Download pdf - Lte Coverage and Capacitry Dimensioning

Long Term Evolution (LTE) Access NetworkCoverage and Capacity Dimensioning

This thesis submitted in partial fulfillment of the requirementsfor thedegree of high diploma in wireless telecommunicationsystem.

Submitted by

● Amr Abdel-Magid Kassab

● Amr Mahmoud Morsy

● Mohammed Mahmoud Mohammed Saad

● Mohamed Mahmoud Mohamed Tantawy

● Mohamed Morsy Mohamed

● Hanaa Abdelmoety Kamel

● Walaa Abd-Elhamid Elawam

Supervised By

Dr.Hamed Abdel Fatah El Shenawy

Cairo 2013

Ministry of Higher Education

National Telecommunication Institute

Electronics and Communications Department

Acknowledgements

First of all, we are grateful to ALLAHALMIGHTY, the most merciful,the most beneficent, who gave us strength, guidance and abilities tocomplete this thesis in a successful manner.

We are thankful to our parents and our teachers that guided us throughoutour career path especially in building up our base in education andenhance our knowledge.

We are indebted to our supervisor Dr. Hamed Abd El Fattah ElShenawyfor his supervision and his co-operation and support really helped uscompleting our project.

Abstract

Long Term Evolution (LTE) is set of enhancement to the currentcellular system in use. LTE is designed to have scalable channelbandwidth up to 20MHz, with low latency and packet optimized radioaccess technology. The peak data rate of LTE is 100 Mbps in downlinkand 50 Mbps in the uplink.

LTE support both FDD and TDD duplexing.

LTE with OFDM technology in the down link, which provideshigher spectral efficiency and more robustness against multipath fading

LTE with SC-FDMA in the uplink LTE

LTE with different MIMO configurations

Dimensioning is initial phase of network planning. It provides estimateof the network elements count as well as the capacity of those elements.The purpose of our project to estimate the required number ofeNodeBs needed to support users with certain traffic load with adesired level of quality of service (QOS) and cover the area ofinterest.

This estimate fulfills coverage requirements and verified for capacityrequirements .

Coverage dimensioning occurs via radio link budget (RLB), maximumallowable propagation path loss (MAPL) is obtained. MAPL is convertedinto cell radius by using appropriate propagation models. The radius ofthe cell is used to calculate the number of sites required to cover the areaof interest. The cell size and the site count are obtained.

Capacity planning deals with the ability of the network to provideservices to certain numbers of users with a desired level of quality ofservice (QOS).

Capacity based site count is compared with coverage based site count.The greater one is selected as the final site count.

Project objectives

Overview of LTE system architecture and specifications Dimensioning of LTE Network Coverage dimensioning via radio link budget and propagation

models Capacity dimensioning Numerical results using Visual Studio and basic language Conclusions and suggestions for future work.

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List of Contents

Item Page

1.0 Chapter One: Overview of LTE 1-1

1.1 Introduction 1-2

2.2 IMT-Advanced 1-2

1.3 LTE specifications 1-4

LTE Architecture 1-15

2.0 Chapter Two: LTE network dimensioning 2-1


2.2 LTE network dimensioning 2-2

2.3 LTE network dimensioning inputs 2-6

2.4 Coverage planning inputs 2-7

2.5 Capacity planning inputs 2-8

2.6 LTE network dimensioning outputs 2-8

2.7 Comparison among dimensioning, planning, optimization 2-9

3.0 Chapter Three: Coverage dimensioning 3-1


3.2 Concepts and Terminology 3-4

3.3 Link Budget Definition 3-5

3.4 Why we use Link Budget? 3-6

3.5 What are the types of Link Budget? 3-6

3.6 Up Link Budget (Up Link coverage) 3-7

3.7 Up Link Budget entries 3-7

3.8 Morphologies Classifications 3-28

3.9 Down Link Budget(Down Link coverage) 3-29

3.10 Down Link limited Link Budget 3-35

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3.11 propagation models 3-37

3.12 Classifications of propagation models 3-39

3.13 Ericsson variant COST 231 Okomara-Hata wave propagation

model

3-42

4.0 Chapter Four: Capacity dimensioning 4-1


4.2 Uplink capacity 4-3

4.3 Downlink capacity 4-6

4.4 Application or service distribution model 4-13

5.0 Chapter Five: numerical results 5-1

5.1 Uplink budget 5-3

5.2 Effects on cell Radius (R) 5-17

5.3 Downlink capacity 5-21

6.0 Chapter Six: conclusion and suggestions for future work 6-1

6.1 Conclusion 6-2

6.2 Suggestions for future work 6-3

iii

List of figures

Items PageFigure(1-1) Overview of IMT advanced 1-2

Figure(1-2) Resource element and resource block 1-14

Figure(1-3) LTE architecture 1-15

Figure(1-4) Evolved Packet System 1-15

Figure(2-1) LTE network planning process 2-2

Figure(2-2) Dimensioning basic steps 2-3

Figure(2-3) LTE network dimensioning inputs 2-6

Figure(2-4) LTE coverage planning 2-7

Figure(2-5) LTE dimensioning outputs 2-9

Figure(2-6) LTE optimization process stages 2-10

Figure(2-7) LTE optimization process 2-11

Figure(2-8) LTE optimization process 2-16

Figure(3-1) LTE Dimensioning Process 3-4

Figure(3-2) Resource Block Definition in Frequency

Domain.

3-11

Figure(3-3) Downlink and Uplink User Scheduling in Time

and Frequency Domain.

3-12

Figure (4.1) channel bandwidth partitioning 4-22

Figure (4-2) subscriber class deployment model 4-29

Figure(5-1) flowchart of effective isotropic radiated power 5-3

Figure(5-2) Effective Isotropic Radiated Power 5-3

Figure(5-3) flowchart of sensitivity of eNodeB 5-5

Figure(5-4) Sensitivity of Enhanced nodeB 5-5

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Figure(5-5) flowchart of Interference Margin 5-7

Figure(5-6) flowchart of Log Normal Fading Margin 5-7

Figure(5-7) flowchart of total margins 5-8

Figure(5-8) Total margin 5-8

Figure(5-9) flowchart of total gains 5-10

Figure(5-10) flowchart of total losses 5-10

Figure(5-11) total gains and total losses 5-11

Figure(5-12) flowchart of maximum allowable path loss 5-12

Figure(5-13) Max. allowable path loss 5-13

Figure(5-14) flowchart of cell radius using Ericson variant

Okumara -Hata

5-14

Figure(5-15) flowchart of site count 5-15

Figure(5-16) cell radius and Site Count 5-15

Figure(5-17) the effect of cell Loading Factor (Q) on the cell

Radius (R) Omni

5-17

Figure(5-18) the effect of cell Loading Factor (Q) on the cell

Radius (R) 3 sector

5-18

Figure(5-19) the effect of morphology on the cell Radius (R)

omni

5-19

Figure(5-20) the effect of morphology on the cell Radius (R) 3

sector

5-20

Figure(5-21) downlink capacity 5-21

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List of tables

Item Page

Table(1-1) Improvement in downlink spectral efficiency going

from 2G to 4G System

1-7

Table (1-2) Targets for average spectrum efficiency 1-8

Table (3-1) Bandwidths and number of physical resource

blocks

3-16

Table(3-2) Channel models specifications 1 3-18

Table (3-3) Channel models specifications 2 3-18

Table(3-4) Channel propagation conditions 3-19

Table(3-5) Maximum Doppler frequency for each channel

model

3-19

Table(3-6) Semi –empirical parameters for uplink 3-21

Table(3-7) Examples of F for varying tilt 3-23

Table(3-8) Lognormal fading margins for varying standard

deviation of log normal fading

3-24

Table(3-9) Values of penetration loss on different morphology

classes

3-26

Table(3-10) Summarizes the features of different morphologies 3-28,

3-29

Table(3-11) Examples of Fc at cell edge for varying tilt 3-33

Table(3-12) Semi –empirical parameters for downlink 3-33

Table(3-14) Fixed attenuation A in Ericsson variant COST 231

Okumara Hata propagation models

3-43

Table(4-1) SINR values corresponding to each modulation

coding scheme (MCS)

4-4

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Table(4-2) semi- empirical parameters for up link 4-5

Table(4-3) Semi- empirical parameters for downlink 4-11

Table (4.5) applications or services distribution model 4-14

Table (4.6) mobile service flows and QoS parameters 4-19

Table (4.7) subscriber class distribution model 4-28

Table (4.8) subscriber class traffic model 4-30

Table (5-1) Default values of User Equipment Effective

Isotropic Radiated Power(EIRP)

5-4

Table(5-2) Default values of Enhanced NodeB sensitivity 5-6

Table(5-3) Default values of total margin 5-9

Table(5-4) Default values of total Gain and losses 5-12

Table(5-5) Default values of Maximum allowable path loss

(MAPL)

5-14

Table(5-6) values of Cell Radius and Site count with

difference Base stations heights

5-16

Table(5-7) The effect of cell Loading Factor (Q) on the cell

Radius (R) Omni

5-17

Table(5-8) The effect of cell Loading Factor (Q) on the cell

Radius (R) 3 sector

5-18

Table(5-9) the effect of morphology on the cell Radius (R)

omni

5-19

Table(5-10) the effect of morphology on the cell Radius (R) 3

sector

5-20

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List of Acronyms and Abbreviations

16QAM: 16 point quadrature amplitude modulation

3GPP: Third Generation Partnership

٦٤QAM: 64 point quadrature amplitude modulation

3G: third generation

4G: fourth generation

AACK: Acknowledgement

AGC: Automatic Gain Control

AP: Access Point

ARQ: Automatic Repeater Request

AUC: Authentication center

A/D: Analog to digital

ADSL: Assymetric Digital Subscriber Line

AMPS: Advanced Mobile Phone Services

AWGN: Additive White Gaussian Noise

BBCH: Broadcast Channel

BPSK: Binary Phase Shift Keying

BSC: Base Station Controller

BTS: Base Transceiver Station

BW: Bandwidth

BER: Bit Error Rate

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CCDMA: Code Division Multiple Access

CW: Continuous Wave

CPL: Car Penetration Loss

COST: Community Collaborative studies in the areas of science and

technology

DDL: Downlink

DSL: Digital Subscriber Line

D/A: Digital to analog

DU: Dense Urban

EEDGE: Enhanced Data Rate for GSM Evolution

EIR: Equipment Identity Register

EIRP: Effective Isotropic Radiated Power

eNodeB: Enhanced NodeB (enhanced base station)

EPA: extended pedestrian

ETU: extended terrestrial

EVA: extended vehicular

EPC: Evolved Packet Core

EPS: Evoved Packet System

FFDD: Frequency Division Duplex

FDMA: Frequency Division Multiple Access

FTT: Fast Fourier Transform

FM: Frequency Modulation

FWLL: Fixed Wireless Local Loop

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FFM: Fast Fading Margin

GGGSN: Gateway GPRS Serving Node

GMSC: Gateway Mobile Switching Center

GMSK: Gaussian Minimum Shift Keying

GSM: Global System for Mobile

GPRS: General Packet Radio Service

GUI: Graphical User Interface

HHARQ: Hybrid Automatic Repeater Request

HLR: Home Location Register

HSCSD: High Speed Circuit Switched Data

HSDPA: High Speed Downlink Packet Access

HSS: Home Subscriber Server

HSUPA: High Speed Uplink Packet Access

IIMS: IP Multimedia Subsystem

IM: Interference Margin

IP: Internet Protocol

KKPI: Key Performance Indicator

LLTE: Long Term Evolution

MMBMS: Multimedia broadcast multicast services

MB-SFN: Multicast/broadcast-single frequency network

x

MIMO: Multi Input Multi Output

MME: Mobile Mobility Management Entity

MRC: Maximal ratio combining

MS: mobile Station

MSC: Mobile Switching Center

MAPL: Maximum Allowable Path Loss

OOFDM: Orthogonal Frequency Division Multiplexing

OMC: Operation and Maintenance Center

PPAPR: Peak -to-average power ratio

PCRF: Policy and Charging Rules Function

PDCCH: Physical downlink control channel

PDN: Public Data Network

PLMN: Public land Mobile Network

PRB: Physical Resource Block

PSK: Phase Shift Keying

PSTN: Public Switched Telephone Network

P-GW: PDN Gateway

PUCCH: Physical Uplink Control Channel

PDCCH: Physical Downlink Control Channel

QQAM: Quadrature Amplitude Modulation

QPSK: Quadrature phase shift Keying

QOS: Quality Of Service

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RRFPA: Radio Frequency Power Amplifier

RNC: Radio Network Controller

RLB: Radio Link Budget

SSC-FDMA: Single Carrier-Frequency Division Multiple Access

SGSN: Serving GPRS Support Node

SIM: Subscriber Identity Module

SINR: Signal Interference -to-noise ratio

S-GW: Serving Gateway

SRVCC: Single Radio Voice Call Continuity

SMS: Short Message Service

SU: Sub Urban

TTDD: Time Division Duplexing

TDMA: Time Division Multiple Access

TMA: Tower Mounted Amplifier

UUE: User Equipment

UL: Uplink

UMTS: Universal Mobile Telecommunication system

UTRAN: UMTS Terrestrial Radio Access Network

VVLR: Visitor Location Register

VOIP: Voice over IP

xii

W

WCDMA: Wideband Code Division Multiple Access

WIMAX: Worldwide Interoperability for Microwave Access

Chapter One

Overview of Long Term Evolution (LTE)

Chapter 1: Overview of Long Term Evolution (LTE)

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Chapter one

Overview of Long Term Evolution (LTE)

1.1. Introduction

LTE is designed to meet users need for high speed data and media

transport as well as high-capacity voice support .The LTE PHY employs

some advanced Technologies that are new to mobile applications these

include OFDMA -SC-FDMA –MIMO. The LTE PHY uses OFDMA in

downlink and SC-FDMA on up link.

Figure (1-1) Overview of IMT Advanced

1.2. IMT-Advanced

International Mobile Telecommunications Advanced (IMT-

Advanced) is requirements issued by the ITU-R of the International

Telecommunication Union (ITU) in 2008 for what is marketed as 4G

mobile phone and Internet access service.


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1.2.1 IMT ADVANCED Requirements

Specific requirements of the IMT-Advanced report included:

1- Based on an all-Internet Protocol (IP) packet switched network

2- Interoperability with existing wireless standards

3- A nominal data rate of 100 Mbit/s while the client physically

moves at high speeds relative to the station,50 Mbit /s in the uplink

and 1 Gbit/s while client and station are in relatively fixed

positions.

4- Dynamically share and use the network resources to support more

simultaneous users per cell.

5- Scalable channel bandwidth 1.4 MHz, 3 MHz, 5 MHz, 15 MHz

and 20 MHz optionally up to 40

6- Peak link spectral efficiency of 15 bit/s/Hz in the downlink, and

6.25bit/s/Hz in the uplink (meaning that 1 Gbit/s in the downlink

should be possible over less than 67 MHz bandwidth)

7- System spectral efficiency of up to 3 bit/s/Hz/cell in the downlink

and 2.25 bit/s/Hz/cell for indoor usage

8- Seamless connectivity and global roaming across multiple

networks with smooth handovers

9- Ability to offer high quality of service for multimedia support

10- support antenna configurations

a- Downlink 4×2, 2×2, 1×2, 1×1

b- Uplink 1×2, 1×1

11- coverage

a- full performance up to 5 km

b-slight degradation 5 km-30 km

c-operation up to 100 km should not be precluded by standard


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12- mobility

a- optimized for low speed less than 15 km per hour

b-high performance at speeds up to 120 km per hour

c-maintain link at speeds up to 350 km per hour

13- LTE support efficient broadcast mode performance :multicast and

broadcast

14- broadcast spectral efficiency 1bit /sec/Hz

15- LTE support paired and unpaired frequency band

16- It support FDD and TDD, half duplex TDD

17- Support adaptive modulation technique: High level and low level

modulation

18- Support scalable FFT size

19- It support turbo code

20- It support low complexity low cost terminal

21- Support VOIP 60 session /Hz/cell

22- Support of cell sizes from tens of meters of radius (femto and Pico

cells) up to over 100 km radius microcells

23- Simplified architecture: The network side of EUTRAN is

composed only by the enodeBs.

24- Low data transfer latencies (sub-5ms latency for small IP packets

in optimal conditions), lower latencies for handover and connection

setup time.

1.3 LTE specifications1.3.1 Peak Rates and Peak Spectral Efficiency

For Data rate many services with lower data rates such as voice

services are important and still occupy a large part of a mobile network’s

overall capacity, but it is the higher data rate services that drive the design


1 - 5

of the radio interface. The ever increasing demand for higher data

rates for web browsing, streaming and file transfer pushes the peak

data rates for mobile systems from kbit/s for 2G, to Mbit/s for 3G and

getting close to Gbit/s for 4G (Erik Dahlman, Stefan Parkvall, and Johan

Sköld, 2011). For marketing purposes, the first parameter by which

different radio access technologies are usually compared is the peak per-

user data rate which can be achieved. This peak data rate generally scales

according to the amount of spectrum used, and, for MIMO systems,

according to the minimum of the number of transmit and receive

antennas.

The peak data rate can be defined as the maximum throughput per user

assuming the whole bandwidth being allocated to a single user with the

highest modulation and coding scheme and the maximum number of

antennas supported. Typical radio interface overhead (control channels,

pilot signals, guard intervals, etc.) is estimated and taken into account for

a given operating point. For TDD systems, the peak data rate is generally

calculated for the downlink and uplink periods separately. This makes it

possible to obtain a single value independent of the uplink/downlink ratio

and a fair system comparison that is agnostic of the duplex mode. The

maximum spectral efficiency is then obtained simply by dividing the peak

rate by the used spectrum allocation.

The target peak data rates for downlink and uplink in LTE Release 8

were set at 100 Mbps and 50 Mbps respectively within a 20 MHz

bandwidth, 7 corresponding to respective peak spectral efficiencies of 5

and 2.5 bps/Hz. The underlying assumption here is that the terminal has

two receive antennas and one transmit antenna. The number of antennas

used at the base station is more easily upgradeable by the network


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operator, and the first version of the LTE specifications was

therefore designed to support downlink MIMO operation with up to four

transmit and receive antennas.

When comparing the capabilities of different radio communication

technologies, great emphasis is often placed on the peak data rate

capabilities. While this is one indicator of how technologically advanced

a system is and can be obtained by simple calculations, it may not be a

key differentiator in the usage scenarios for a mobile communication

system in practical deployment. Moreover, it is relatively easy to design a

system that can provide very high peak data rates for users close to the

base station, where interference from other cells is low and techniques

such as MIMO can be used to their greatest extent. It is much more

challenging to provide high data rates with good coverage and mobility,

but it is exactly these latter aspects which contribute most strongly to user

satisfaction.

In typical deployments, individual users are located at varying

distances from the base stations, the propagation conditions for radio

signals to individual users are rarely ideal, and the available resources

must be shared between many users. Consequently, although the claimed

peak data rates of a system are genuinely achievable in the right

conditions, it is rare for a single user to be able to experience the peak

data rates for a sustained period, and the envisaged applications do not

usually require this level of performance. A differentiator of the LTE

system design compared to some other systems has been the recognition

of these „typical deployment constraints‟ from the beginning. During the

design process, emphasis was therefore placed not only on providing a

competitive peak data rate for use when conditions allow, but also


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importantly on system level performance, which was evaluated during

several performance verification steps.

System-level evaluations are based on simulations of multicell

configurations where data transmission from/to a population of mobiles is

considered in a typical deployment scenario. The sections below describe

the main metrics used as requirements for system level performance. In

order to make these metrics meaningful, parameters such as the

deployment scenario, traffic models, channel models and system

configuration need to be defined (Stefanie Sesia, Issam Toufik and

Matthew Baker, 2011).

Table (1-1): Improvement in downlink spectral efficiency going from 2G

to 4G System

1.3.2 Spectrum efficiency

In this section, the target for peak spectrum efficiency, the average

spectrum efficiency, and cell edge spectrum efficiency are defined. The

target for average spectrum efficiency and the cell edge user throughput

efficiency should be given a higher priority than the target for peak

spectrum efficiency and VoIP capacity. The target for average spectrum


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efficiency and the cell edge spectrum efficiency should be achieved

simultaneously.

The peak spectrum efficiency is the highest data rate normalized by

overall cell bandwidth assuming error-free conditions, when all available

radio resources for the corresponding link direction are assigned to a

single UE. The system target to support downlink peak spectrum

efficiency of 30 bps/Hz and uplink peak spectrum efficiency of 15

bps/Hz. Assumption of antenna configuration is (8x8) or less for DL and(

4x4) or less for UL Average spectrum efficiency is defined as the

aggregate throughput of all users (the number of correctly received bits

over a certain period of time) normalized by the overall cell bandwidth

divided by the number of cells. The average spectrum efficiency is

measured in b/s/Hz/cell. Advanced E-UTRA should target the average

spectrum efficiency to be as high as possible, given a reasonable system

complexity. The expectation at the end of the study item is that the values

of all the targets (of the different configurations) will be made available,

but currently the evaluation for the blanked out boxes in the table below,

are a lower priority. Advanced E-UTRA should target the average

spectrum efficiencies in different environments in Table (2-2).

Table (1-2): Targets for average spectrum efficiency


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1.3.3 Cell edge user throughput

The cell edge user throughput is defined as the 5% point of CDF of

the user throughput normalized with the overall cell bandwidth.

Advanced E-UTRA should target the cell edge user throughput to be as

high as possible, given a reasonable system complexity.

A more homogeneous distribution of the user experience over the

coverage area is highly desirable and therefore a special focus should be

put on improving the cell edge performance.

The expectation at the end of the study item is that the values of all the

targets (of the different configurations) will be made available, but

currently the evaluation for the blanked out boxes in the table below, are

a lower priority. Advanced E- UTRA should target the cell edge user

throughput below in different environments

1.3.4 Voice Capacity (VOIP)

VoIP services convert your voice into a digital signal that

travels over the Internet. If you are calling a regular phone number, the

signal is converted to a regular telephone signal before it reaches the

destination. VoIP can allow you to make a call directly from a computer,

a special VoIP phone, or a traditional phone connected to a special

adapter. In addition, wireless "hot spots" in locations such as airports,

parks, and cafes allow you to connect to the Internet and may enable you

to use VoIP service wirelessly.

Some VoIP providers offer their services for free, normally only for

calls to other subscribers to the service. Your VoIP provider may permit

you to select an area code different from the area in which you live. It


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also means that people who call you may incur long distance charges

depending on their area code and service.

Some VoIP providers charge for a long distance call to a number outside

your calling area, similar to existing, traditional wire line telephone

service. Other VoIP providers permit you to call anywhere at a flat rate

for a fixed number of minutes.

Depending upon your service, you might be limited only to other

subscribers to the service, or you may be able to call anyone who has a

telephone number - including local, long distance, mobile, and

international numbers. If you are calling someone who has a regular

analog phone, that person does not need any special equipment to talk to

you. Some VoIP services may allow you to speak with more than one

person at a time. Some VoIP services offer features and services that are

not available with a traditional phone, or are available but only for an

additional fee. You may also be able to avoid paying for both a

broadband connection and a traditional telephone line. If you're

considering replacing your traditional telephone service with VoIP, there

are some possible differences. Some VoIP services don't work during

power outages and the service provider may not offer backup power. Not

all VoIP services connect directly to emergency services through 9-1-1.

For additional information VoIP providers may or may not offer directory

assistance/white page listings.

1.3.5 Mobility

The system shall support mobility across the cellular network for

various mobile speeds up to 350km/h (or perhaps even up to 500km/h

depending on the frequency band). System performance shall be


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enhanced for 0 to 10km/h and preferably enhanced but at least no worse

than E-UTRAand E-UTRAN for higher speeds.

1.3.6 Control Plane and User Plane Latency

Control plane deals with signaling and control functions, while

user plane deals with actual user data transmission. C-Plane latency is

measured as the time required for the UE (User Equipment) to transit

from idle state to active state. In idle state, the UE does not have an

Reconnection.

Once the RRC is setup, the UE transitions to connected state and then to

the active state when it enters the dedicated mode. U-Plane latency is

defined as one way state when it enters the dedicated mode. U-Plane

latency is defined as one-way transmit time between a packet being

available at the IP layer in the UE/E-UTRAN (Evolved UMTS Terrestrial

Radio Access Network) edge node and the availability of this packet at

the IP layer in the EUTRAN/ UE node.

U-Plane latency is relevant for the performance of many applications.

This tutorial presents in detail the delay budgets of C-Plane and U-Plane

procedures that add to overall latency in state transition and packet

transmission. Latency calculations are made for both FDD and TDD

modes of operation. Technical details of C-Plane and U-Plane latency

.This tutorial is organized as follows: Requirements and assumptions in

Section This tutorial presents in detail the delay budgets of C- Plane and

U-Plane procedures that add to overall latency in state transition and

packet transmission. Latency calculations are made for both FDD and

TDD modes of operation. Technical details of C-Plane and U-Plane

latency are cited in This tutorial is organized as follows: Requirements


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and assumptions in Section II, C- Plane latency analysis in Section III and

U-Plane latency analysis in Section IV. The conclusions are summarized

in Section V. All the values indicated in the tables are in mill seconds

(ms). The method of calculating these latencies is illustrated in the

appendix.

Low latency where5 ms user plane latency for small IP packets (user

equipment to radio access network [RAN] edge) .100 ms camped to

active. 50 ms dormant to active.

Scalable bandwidth where the 4G channel offers four times more

bandwidth than current 3G systems and is scalable. So, while 20 MHz

channels may not be available everywhere, 4G systems will offer channel

sizes down to 5 MHz, in increments of 1.5 MHz.

1.3.7 Spectrum Allocation and Duplex Modes

Transmission techniques exist

Simplex

One party transmits data and the other party receives data.No

simultaneous transmission is possible, the communication is one-way and

only one frequency (channel) is used.

Half Duplex

Each party can receive and transmit data, but not at the same time. The

communication is two-way and only one frequency (channel) is used.

Full Duplex

Each party can transmit and receive data simultaneously.


1 - 13

The communication is two-way and two frequencies.

Full duplex main methods used are

Time Division Duplexing (TDD)

The communication is done using one frequency, but the time for

transmitting and receiving is different. This method emulates full duplex

communication using a half-duplex link.

Frequency Division Duplexing (FDD)

The communication is done using two frequencies and the transmitting

and receiving of data is simultaneous.

The advantages of TDD are typically observed in situations uplink and

downlink data transmissions are not symmetrical. Transmitting and

receiving is done using one frequency, the channel estimations for beam

forming (and other smart antenna techniques) apply for both the uplink

and the downlink.

A typical disadvantage of TDD is the need to use guard periods between

the downlink and uplink transmissions. The advantages of FDD are

typically observed in situations where the uplink and downlink data

transmissions are symmetrical (which is not usually the case when using

wireless phones). More importantly, when using FDD, the interference

between neighboring Radio Base Stations (RBSs) is lower than when

using TDD. Also, the spectral efficiency (which is a function of how well

a given spectrum is used by certain access technology) of FDD is greater

than TDD.


1 - 14

Frequency band from 2600MHz to 2.6 GHz. Channel bandwidth up to 20

MHz Channel bandwidth on-demand (1.4 MHz, 3MHz, 5MHz,

10MHz, 15MHz, 20MHz). Charging / volume

1.3.8 Resource element and resource block

A resource element is the smallest unit in the physical layer and

occupies one OFDM or SC-FDMA symbol in the time domain and

one subcarrier in the frequency domain as shown in figure (2-1) .

Aresource block (RB) is the smallest unit that can be scheduled for

transmission. An RB physically occupies 0.5 ms (1 slot) in the time

domain and 180 KHz in the frequency domain .the number of

subcarriers per RB and the number of symbols per RB vary as a

function of the cyclic prefix length and subcarrier spacing.

Figure (1-2): Resource element and resource block


1 - 15

1.4 LTE architecture

Figure (1-3) LTE architecture

The combination of the EPC and the evolved RAN ( E-UTRAN) is the

evolved packet system (EPS).

Figure (1-4) Evolved Packet System


1 - 15







1 - 15







1 - 16

1.4.1 Access network

E-UTRAN

Consists only of enodeBs on the network side. The enodeB performs

tasks similar to those performed by the nodeBs and RNC (radio network

controller) together in UTRAN. The aim of this simplification is to

reduce the latency of all radio interface operations.

The eNBs are interconnected with each other by means of the X2

interface. The eNBs are connected by the S1 interface to the EPC

(Evolved Packet Core). The eNB connects to the MME (Mobility

Management Entity) by means of the S1-MME interface and to the

Serving Gateway (S-GW) by means of the S1-U interface. The S1

interface supports a many-to-many relation between MMEs / Serving

gateways and eNBs.

eNodeB

eNB interfaces with the UE and hosts the Physical (PHY), Medium

Access Control (MAC), Radio Link Control (RLC), and Packet Data

Control Protocol (PDCP) layers. It also hosts Radio Resource Control

(RRC) functionality corresponding to the control plane. It performs many

functions including radio resource management, admission control,

scheduling, enforcement of negotiated UL QoS, cell information

broadcast, ciphering/deciphering of user and control plane data, and

compression/decompression of DL/UL user plane packet headers.

Functions of eNodeB

Transmission & Reception


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Modulation & Demodulation

Radio resources allocation

Error Detection and Correction

Connectivity to the EPC

Header Compression & packet encryption

Scheduling and transmission of broadcast information

1.4.2 CORE NETWORK ( EPC )

The main logical nodes of the EPC are:

Mobility Management Entity (MME)

PDN Gateway (P-GW)

Policy and Charging Rules Function (PCRF)

Serving Gateway (S-GW).

Home Subscriber Server (HSS)

1- MME

Mobility Management Entity is the control node that processes the

signaling between the UE and the CN. Manages and stores UE context

(for idle state: UE/user identities, UE mobility state, user security

parameters). It generates temporary identities and allocates them to UEs.

Security Procedures (by interacting with the HSS).

Idle mode UE Tracking Area update & Paging

Handling QoS


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Choosing the SGW for a UE at the initial attach and at time of

intra-LTE handover involving Core Network node relocation.

2-P-GW

The PDN GW provides connectivity to the UE to external packet

data networks by being the point of exit and entry of traffic for the UE

The Packet data network gateway is responsible for:

IP address allocation for the UE

Charging (according to rules from the PCRF )

Filtering of downlink user IP packets into the different QoS based

bearers

mobility anchor for interworking with non-3GPP technologies such

as CDMA2000 and WiMAX networks

3-PCRF

The Policy and Charging Rules Function is responsible for :

Real time Determination of policy & charging rules

QoS handling.

4-S-GW

The SGW routes and forwards user data packets, while also acting

as the mobility anchor for the user plane during inter-eNB handovers and

as the anchor for mobility between LTE and other 3GPP technologies

(terminating S4 interface and relaying the traffic between 2G/3G systems

and PDN GW).


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The serving gateway is responsible for:

Routes and forwards user data packets

Mobility anchor for intra E-UTRAN mobility (when the UE

moves between eNodeBs)

Mobility anchor with 2G/GSM and 3G/UMTS mobility.

5-HSS

Users subscription data

Information about the PDNs to which the user can connect

The identity of the MME to which the user is currently

attached or registered

Authentication information

Chapter TwoLTE network dimensioning

Chapter 2: LTE network dimensioning

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Chapter TwoLTE network dimensioning

2.1 Introduction

Dimensioning is a part of the whole planning process, which alsoincludes detailed planning and optimization of the wireless cellularnetwork as shown in figure: (2-1)

Figure: (2-1) LTE network planning process

2.2 LTE network dimensioning

It is the initial phase of network planning. It provides the firstestimate of the network element count as well as the capacity of thoseelements. The purpose of dimensioning is to estimate the requirednumber of eNodeBs needed to support a specified traffic load in an area.The aim of this whole exercise is to provide a method to design thewireless cellular network such that it meets the requirements set forth bythe customer. This process can be modified to fit the needs of anywireless cellular network. This is a very important process in networkdeployment. Wireless cellular network dimensioning is directly related tothe quality and effectiveness of the network. And can deeply affect itsdevelopment. Wireless cellular network dimensioning follows basic stepsshown in figure:

Coverage planning and siteselection and acquisition

Requirements andstrategy for

coverage, capacityand quality Capacity requirement

Parameter planning

Performanceanalysis in terms ofquality, efficiency

and availability

Dimensioning OptimizationPlanning


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Figure (2-2): Dimensioning basic steps

2.2.1 Data and Traffic analysis

This is the first step in LTE dimensioning. It involves gathering ofrequired inputs and their analysis to prepare them for use in LTEdimensioning process.

Operator data and requirements are analysed to determine the bestsystem configuration. Wireless cellular dimensioning requires somefundamental data elements. These parameters include subscriberpopulation, traffic distribution, geographical area to be covered,frequency band, allocated bandwidth, and coverage and capacityrequirements. Propagation models according to the area and frequencyband should be selected and modified if need. This is necessary forcoverage estimation.

System specific parameters like, transmit power of the antennas, theirgains, estimate of system losses, type of antenna system used etc., mustbe known prior to the start of wireless cellular network dimensioning.Each wireless network has its own set of parameters.

Traffic analysis gives an estimate of the traffic to be carried by thesystem. Different types of traffic that will be carried by the network aremodulated. Traffic types may include voice calls, VOIP, PS or CS traffic.Overheads carried by each type of traffic are calculated and included inthe model. Time and amount of traffic is also forecasted to evaluate theperformance of the network and to determine whether the network canfulfil the requirements set forth.

Dimensioning steps

Data/TrafficAnalysis

Coverageestimation

CapacityEvaluation

TransportDimensioning


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2.2.2 Coverage estimation

It is used to determine the coverage area of each eNodeB. Coverageestimation calculates the area where eNodeB can be heard by the users(receivers). It gives the maximum area that can be covered by eNodeB.But it is not necessary that an acceptable connection (e.g a voice call)between eNodeB and receiver can be established in coverage area.However eNodeB can be detected by the receiver in coverage area.

Coverage analysis fundamentally remains the most critical step in thedesign of LTE network as with 3G systems. RLB (Radio Link Budget) isat the heart of coverage planning which allows the testing of path lossmodel and the required peak data rates against the target coverage levels.

The result is the effective cell range to work out the coverage-limitedsite count. This requires the selection of appropriate propagation model tocalculate path loss.

LTE RLB with the knowledge of cell size estimates and of the area tobe covered is an estimate of the total number of sites is found. Thisestimate is based on coverage requirements and needs to be verified forthe capacity requirements.

Coverage planning includes radio link budget and coverage analysisRLB comprises of all the gains and losses in the path of the signal fromtransmitter to receiver. This includes transmitter and receiver gains aswell as losses and the effect of the wireless medium between them. Freespace propagation loss, fast fading and slow fading in taken into account.Additionally, parameters that are particular to some systems are alsoconsidered. Frequency hopping and antenna diversity margins are twoexamples.

2.2.3 Capacity evaluation

Capacity planning deals with the ability of the network to provideservices to the users with a desired level of quality. After the sitecoverage area is calculated using coverage estimation, capacity relatesissues are analyzed. This involves selection of site and systemconfiguration, e.g. channels used channel elements and sectors.

These elements are different for each system. Configuration is selectedsuch that it fulfils the traffic requirements. In some wireless cellularsystems, coverage and capacity are interrelated, e.g. in WCDMA.


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In this case, data pertaining to user distribution and forecast ofsubscriber’s growth is of almost importance.

Dimensioning team must consider these values as the have directimpact on coverage and capacity, Capacity evaluation gives an estimateof the number of sites required to carry the anticipated traffic over thecoverage area.

Once the number of sites according to the traffic forecast isdetermined, the interfaces of the network are dimensioned. Number ofinterfaces can vary from a few in some systems to many in others. Theobjective of this step is to perform the allocation of traffic in such a waythat no bottle neck is created in the wireless network. All the quality ofservice requirements are to be met and cost has to be minimized. Goodinterface dimensioning is very important for smooth performance of thenetwork.

With a rough estimate of the cell size and site count, verification ofcoverage analysis is carried out for the required capacity. It is verifiedwhether with the given site density, the system can carry the specifiedload or new sites have to be added. In LTE, the main indicator of capacityis SINR distribution in the cell.

This distribution is obtained by carrying out system levels simulations.SINR distribution can be directly mapped into system capacity (datarate). LTE cell capacity is impacted by several factors, for example,packet scheduler implementation, supported MCSs, antennaconfigurations and interference level. Therefore, many sets of simulationresults are required for comprehensive analysis. Capacity based site countis then compared with coverage result and greater of the two numbers isselected as the final site count, as already mentioned in the previoussection.

2.2.4 Transport Dimensioning

Transport dimensioning deals with the dimensioning of interfacesbetween different network elements. In LTE, S1 (between eNodeB and aGW) and X2 (between two eNodeBs) are the two interfaces to bedimensioned. These interfaces were still in the process of beingstandardized at the time of this work. Therefore, transport dimensioningis not included in this thesis work.


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An initial sketch of LTE network is obtained by following the abovementioned steps of dimensioning exercise. This initial assessment formsthe basis of detailed planning phase. In this thesis, main emphasis is onsteps two to four.

First step is unnecessary because the data for the test cases is takenfrom WIMAX scenario, allowing its by pass. Coverage and capacityplanning is dealt in detail and resulting site count is calculated to give anestimate of the dimensioned LTE network. Dimensioning of LTE willdepend on the operator strategy and business case. The physical side ofthe task means to find the best possible solution of the network whichmeets operator requirements and expectations. In detail and resulting sitecount is calculated to give an estimate if the dimensioned LTE network.

Dimensioning of LTE will depend on the operator strategy andbusiness case. The physical side of the task means to find the bestpossible solution of the network which meets operator requirements andexpectative.

2.3 LTE network dimensioning inputs

LTE dimensioning inputs used in the development of methods andmodels for LTE dimensioning. LTE dimension inputs can be broadlydivided into three categories; quality, coverage and capacity relatedinputs. LTE network dimensioning has three main processes shown infigure (2-3).

Figure (2-3): LTE network dimensioning inputs

2.3.1 Quality inputs

Dimensioning inputs

Coverage planning inputsQuality inputs Capacity planning inputs


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Quality inputs include average cell throughput and blocking probability.These parameters are the customer requirements to provide a certain levelof service to its users. These inputs directly translate into Qos parameters.Besides cell edge coverage probability is used in the dimensioning tool todetermine the cell radius and thus the site count.

Three methods are employed to determine the cell edge. These includeuser defined maximum throughput at the cell edge, maximum coveragewith respect to lowest MCS (giving the minimum possible site count) andpredefined cell radius. With a predefined cell radius, parameters can bevaried to check the data rate achieved at this cell size. This option givesthe flexibility to optimize transmitted power and determining a suitabledata rate corresponding to this power.

2.4 Coverage planning inputs

Required coverage probability plays a vital role in determination of callradius. Even a minor change in coverage probability causes a largevariation in cell radius as shown in figure (2-4)

Figure (2-4): LTE coverage planning

LTE dimensioning inputs for coverage planning exercise are similarto the corresponding inputs for 3G UMTS networks.

Radio link budget (RLB) is of central importance to coverageplanning in LTE.

Radio Link budget(RLB)

MAPL

Propagation model

Cell size


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RLB inputs include transmitter and receiver antenna systems, numberof antennas used, conventional system gains and losses, cell loading andpropagation models. LTE can operate in both the conventional frequencybands of 900 and 1800 MHz as well as extended band of 2600 MHz.Models for all the three possible frequency bands are incorporated in thiswork. Additionally, channel types (pedestrian, Vehicular) andgeographical information is needed to start the coverage dimensioningexercise. Geographical input information consists of area typeinformation (Urban, Rural, etc.) and size of each area type to be covered.Furthermore, required coverage probability plays a vital role indetermination of cell radius. Even a minor change in coverage probabilitycauses a large variation in cell radius.

2.5 Capacity planning inputs

Capacity planning inputs provides the requirements, to be met by LTEnetwork dimensioning exercise. Capacity planning inputs gives thenumber of subscribers in the system, their demanded services andsubscriber usage level. Available spectrum and channel bandwidth usedby the LTE system are also very important for LTE capacity planning.

Traffic analysis and data rate to support available services (Speech,Data) are used to determine the number of subscribers supported by asingle cell and eventually the cell radius based on capacity evaluation.

LTE system level simulation results and LTE link level simulationresults are used to carry out capacity planning exercise along with otherinputs. These results are obtained from Nokia's internal sources.Subscriber growth forecast is used in this work to predict the growth andcost of the network in years to come. This is a marketing specific inputtargeting the feasibility of the network over a longer period of time.Forecast data will be provided by the LTE operators.

2.6 LTE network dimensioning outputs

Outputs or targets of LTE dimensioning process have already beendiscussed indirectly in the previous section. Outputs of the dimensioningphase are used to estimate the feasibility and cost of the network. Theseoutputs are further used in detailed network planning. Dimensioning LTEnetwork can help out LTE core network team to plan a suitable networkdesign and to determine the number of backhaul links required in thestarting phase of the network as shown in figure (2-5)

Cell size is the main output of LTE dimensioning exercise.


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Two values of cell radius are obtained, one from coverage evaluationand second from capacity evaluation. The larger of the number is takenas the final output. Cell radius is then used to determine the number ofsites. Assuming a hexagonal cell shape, number of sites can be calculatedby using simple geometry. This procedure is explained capacities ofeNBs are obtained from capacity evaluation, along with the number ofsubscribers supported by each cell. Interface dimensioning is the last stepin LTE access network dimensioning, which is out of scope of this thesiswork. The reason is that LTE interfaces (S1 and S2) were still undergoingstandardization.

Figure (3-5): LTE dimensioning outputs

2.7 Comparison among dimensioning, planning and optimization.

Dimensioning is the initial phase of network planning. It provides thefirst estimate of the network element count as well as the capacity ofthese elements. The purpose of dimensioning is t estimate the requirednumber of the radio base stations needed to support a specified trafficload in an area.

The radio network planning process is designed to maximize thenetworks coverage, whilst at the same time providing the desiredcapacity. In order to achieve this, there are number of stages that are

DimensioningOutputs

Population statistics

Number of subscribes

Area to be covered by thenetwork

Subscriber geographical spread

Cell throughput

Final site-count


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typically performed, these include: Initial Planning, Detailed Planningand Optimization.

Optimization is probably the most important stage when planning anLTE network. Typically it can be split into pre-launch optimization.There are however a number of different areas that may be optimized,these include.

Figure (2-6) optimization stages of LTE

2.7.1 Planning of LTE

The radio network planning process is designed to maximize thenetworks coverage, whilst at the same time providing the desiredcapacity. In order to achieve this, there are a number of stages that aretypically performed, these include:

Nominal or preliminary planning Detailed planning Optimization


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Figure (2.7) the cellular network planning processes

2.7.1.1 Nominal or preliminary cell planning

A nominal or preliminary cell plan can be produced from thedata compiled from coverage and traffic analysis. The nominal cell plainsa graphical representation of the network and looks like a cell pattern on amap. During nominal cell planning, do not care about the position of thesites taking only in consideration the separation distance between sites.

To simplify the network planning, hexagonal shaped cells are adoptedalthough they are artificial or fictitious and do not exist in real world butit have become a widely promoted symbols for cellular structured system.Nominal cell plans are the first cell plans and forms the basis for furtherplanning.

In reality, each company has a planning tool which is a work stationequipped with a software package based on link budget calculations andusing certain propagation model to determine the cell radius and theresults are displayed on the map using different colors. An up to datedigital three dimensional map with high resolutions for the area where thenetwork is to be planned is used to import the actual environment datathat include the terrain fluctuations (height information), clutterdistribution, dense degree of the area of interest. The area of interest is


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divided into different sub regions according to different environmentdefinitions. Each sub region has its own characteristics. The classificationis based on the dense of buildings and their heights in the sub region.

Each sub region is classified into one of the four categories: denseurban (DU), urban (UR), suburban (SU) and rural (RU).The planning tooldetermines the classification of each sub region. It is possible to importdata from site survey files. Data can also be imported from fieldmeasurements files to tune the propagation model as will be explained inthe following subsections.

The area where the network is to be planned to be covered withcellular structured system is used. Two study cases are investigated:

Coverage oriented environment represent suburbanand rural environments.

Capacity oriented environment represent dense urbanand urban environments.

Using the software program developed by us the maximum allowablepath loss (MAPL) is calculated using reverse link budget and forwardlink budget and the link balance was made and the least value was takenas an input to the propagation model. Thus, the cell radius was calculatedusing coverage criterion. The classification of sub regions according totheir building density and heights is determined by us during site surveyby observing the area features, landmarks and terrain in each sub region.

2.7.2 Detailed planning

2.7.2.1 Site surveysOnce the nominal cell planning has been completed, site surveys

can be performed for all the proposed site locations by the site surveyteam. The site survey includes: site search, candidate sites are chosen, thesite survey team check the validity of each location of the sites, contactwith the site owner, site location lease agreement, get permission of thenew sites, and carry out the construction of the civil works, towererection, transmission and interconnection between the network entities.Finally site acquisition.

The following items must be checked for each site:

The space for the equipment including: antennas, cable runs andpower facilities. The exact site locations (with some shifts)are fed back tothe network planning team to modify the network planning by shifting the


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locations of the sites such that no dead zones were introduced and overlapbetween sites were reduced as much as possible.

2.7.2.2 Field measurementsThe purpose of the field measurements is to correct the propagation

model to reflect the propagation status of wireless signal in theenvironment of the area of interest, thus making the model more practicalmeet the coverage requirement.

To conduct field tests, the following steps have to be followed:You have to choose the frequency of the measurement. If there is

interference on the frequency point to be used, choose a frequency pointwithout interference. The transmission characteristics are almost the samewhen frequency difference is 10 MHz or so.

Field measurements site choice: You have to choose the fieldmeasurements site. The field measurements site should not be too muchhigher than the surrounding buildings and 10 meters are suitable. Toobtain as much data as possible for correcting various clutters, two orthree field measurements sites with similar surrounding clutters(building heights, site height, and so on) can be chosen to carry out fieldmeasurements and data from several sites can be synthesized to executethe correction of the various clutters.

Choose pertinent parameters of the field measurements site i.e. useomnidirectional antenna, choose proper transmission power, noobstruction surrounding the field measurements site, and clean thefrequency point.

The tools for field measurements includes: transmitter or CWtransmitter, scanner or field strength meter and GPS handset.

Before field measurements, you have to span antennas,install transmitter, and adjust output power and frequency point to propervalues and transmitting signal.

After field measurements, the field measurements data is put into aform acceptable for the planning tool load the field measurements fileinto the planning tool and correct the model.

2.7.2.3 System design (or final cell plan)The actual and the exact site locations are used to produce the final cell

planning which is used for network installations, provided that no deadzones and overlap between sites is small as possible 2.5 System diagnosisThe test team via the driving test and using test mobile system which is atesting tool. The testing tool includes mobile test units (MTUs) in carsand fixed test units geographically distributed. The testing tool consists ofa MS with special software, a portable personal computer (PC) and a


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global positioning system (GPS) receiver and mobile traffic recording(MTR) and cell traffic recording (CTR). The MS is used in active andidle mode. The PC is used for presentation, control and measurementdata storage. The GPS receiver provides the exact position of themeasurement site by utilizing satellites. When the satellite signals areshadowed, the GPS system switches to dead reckoning. Dead reckoningconsists of a speed sensor and a gyro. This provides the position ifsatellite signals are lost temporarily. The measurement data can beimported to the planning tool and can be displayed on a map to comparethe measured handoffs with the predicted cell boundaries for example tocheck the network performance, to evaluate the customer complaints, toverify that the final cell planning was implemented successfully.

2.7.2.4 System tuningAfter installation of the network, it is continuously monitored to

determine how well it meets the coverage and capacity requirement usingthe measured data, parameters are changed. Other measurements can betaken if necessary.

The parameters to be changed are such as eNodeB transmitted power,eNodeB antenna height, antenna down tilting angle, antenna type (gain,horizontal HPBW, and so on). Change handoff parameters, change, addor decrease channels.

2.7.2.5 System growthCell planning is an ongoing process. If the network needs to be

expanded to extend coverage due to increase in traffic of because orchange in the environment Starting with a new capacity or traffic andcoverage or power analysis.

2.7.2.6 eNodeB site choiceWhen choosing eNodeB site, the following rules should be obeyed:

1) Antenna height should be higher to some degree than thesurroundings.

2) Ensure that there is no obvious obstruction insurrounding environments.

3) Ensure that there is no obstruction surrounding the position ofsetting the global positioning (GPS) antenna.

4) Meet coverage goal requirement concerning the effectivecoverage of the eNodeB.

5) Predict traffic distribution in the coverage area and set theeNodeB sites on the places of real traffic need.


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6) Utilize existent sites such as telecom Egypt centrals in case ofrural communication network and use other communicationresources as possible such as towers, buildings.

7) Guarantee necessary space separation concerning theinterference from other systems.

8) Avoid strong wireless transmitter, radar or other seriousinterference.

9) Choose places with convenient traffic, reliable electricity plant,if not available use generators or solar cell panels

10) Avoid being near the flammable or explosive buildings.11) Avoid being near the industrial manufactories with

poisonous gas or smoke and dust.12) Avoid hospitals, educational buildings, military zones,

church, mosques, and entertainment areas.

2.7.2.7 Antenna configuration and cell type choiceThe choice of eNodeB antenna should concern with the followingfactors: site type, dense degree of eNodeB and relative positionsbetween them and dense degree of the area and so on. Thefollowing rules should be obeyed when choosing antennas:1) In dense urban (DU) and urban (UR) areas i.e. in capacity

oriented areas, sectorized cells or directional antennas withnarrow power beam width (HPBW) angle can be chosen andlarge gain can be chosen to reduce the other cell interference andincrease the capacity.

2) In suburban areas and rural areas with low capacity where useror population density is low i.e. In coverage oriented areas,Omni cells with omnidirectional antennas with high antennaheight can be chosen.

3) In suburban areas and rural areas, when the capacity increases,directional antennas with wide half power beam width (HPBW)angle and large gain value can be chosen to increase coverage.

4) In highways, where there is no need to cover towns along theroad, or at border area or at the coast, 2 sector configuration isthe optimal solution with two directional antennas with narrowerwidth and higher gain antennas.

5) Three sector cells is the optimum solution to meet both capacityand coverage in all morphologies.

6) Dual polarization is usually used in dense urban (DU) and urban(UR) areas and space diversity is usually used in suburban (SU)rural (RU) areas.


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2.7.3 LTE optimization

Optimization is probably the most important stage when planning LTEnetwork. Typically it can be split into pre-launch optimization andpost-launch optimization. There is however a number of different areasthat may be optimized these including:

Capacity Coverage Configuration and parameters Interference

Prelaunching optimization

It is done when the sites are on air but not available to users. It is donevia drive test to determine gaps and holes for coverage and to ensureoptimal operation for the network and to verify coverage, capacity andquality requirements.

Figure (2-8) LTE optimization process


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Chapter Three

Coverage Dimensioning

Chapter 3: Coverage dimensioning

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Chapter Three

Coverage dimensioning3.1 Introduction

The link budget calculations estimate the maximum allowed signal

Attenuation, called path loss, between the mobile and the base station

antenna. The maximum path loss allows the maximum cell range to be

estimated with a suitable propagation model, such as Okumura–Hata. The

cell range gives the number of base station sites required to cover the

target geographical area. The link budget calculation can also be used to

compare the relative coverage of the different systems.

Network dimensioning requires determination the number or cells

(number of sites) to cover a certain region and to determine the radius of

each cell and the spacing between them either using traffic or coverage

criteria. So, in this chapter we will discuss the coverage analysis using

the link budget and certain propagation model.

This chapter presents the outline and basic concepts required to

dimension coverage in the Long Term Evolution (LTE) network with

functions in the current release. The method presented in this document

consists of concepts and mathematical calculations that are elements of a

general dimensioning process.

The detailed order and flow of calculations depends on the required

output of and type of input for the specific dimensioning task. The

method provides a specific dimensioning process example. By changing

the prescribed inputs and outputs and the order of calculations, the

dimensioning process can be adapted to other methods.


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Input requirements for the capacity and coverage dimensioning

process consist of a bit rate at the cell edge, one for downlink and one for

uplink.

The required output is site-to-site distance and cell capacity in the

uplink and downlink. The method is developed for Frequency Division

Duplex (FDD), but can also be used for Time Division Duplex (TDD) .

Limitations

Limitations to the calculation method include the following:

Multiple Inputs Multiple Outputs (MIMO) is considered only for

the downlink for a maximum of two antennas

Outer loop power control in the uplink is not modelled

The method is adapted and developed primarily as a mobile

broadband service that can handle Voice over IP (VoIP) to a limited

extent

Quality of Service (QoS) is not handled by the method

Assumptions

Calculations for coverage and capacity are based on the following

assumptions:

All user equipment is assumed to have two receiving antennas

All resource blocks are transmitted at the same power, including

user data, as well as control channels and control signals

The coverage for control channels and control signals equals that

of user data at the same power.

Layer 1 overhead for all control channels and control signals is

included in the Signal-to-Interference-and-Noise Ratio (SINR) to

bit rate relationships.


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Figure (3-1) LTE Dimensioning Process

3.2 Concepts and Terminology

The following terms are used in describing capacity and coverage

dimensioning:

Average user bit rate

The bit rate achievable by a single user. When all resources in a cell

are used, the average user bit rate can be the average throughput in one

cell. It is a measure of average potential in a cell while all interfering cells

are loaded to the dimensioned level.

Cell edge

The geographical location where the path loss between eNodeB and

the antenna is at a specific maximum threshold value, as calculated using

the quality requirement imposed on the network, guaranteeing the

required quality with a probability of 95%, for example.

Cell throughput

Cell throughput is obtained in one cell when all cells are loaded to

the dimensioned level, and the resource use is equal to system load,


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dimensioning:






Cell edge





Cell throughput




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dimensioning:






Cell edge





Cell throughput




3 - 5

interfering cells as well as interfered cells. It is the average throughput

per cell as calculated across the entire network.

Coverage (area)

The percentage of cell area that can be served according to a defined

quality requirement. With an assumed uniform subscriber density (often

assumed in a dimensioning exercise), the percentage of served area

equals the percentage of served users.

Resource block

It is the smallest unit in the physical layer and occupies one OFDM

or SC-FDMA symbol in the time domain and one subcarrier in the

frequency domain. A two-dimensional unit in the time-frequency plane,

Consisting of a group of 12 carriers, each with 15 kHz bandwidth, and

one slot of 0.5 ms.

System load

The extent of available air interface resource usage.

The system load equals the ratio of used resource blocks as an average

over the entire system.

3.3 link Budget Definition

Illustrative example: you are planning a vacation .You estimate that

you will need 1000 L.E to pay for the hotels, restaurant, food etc.. You

start your vacation and watch the money get spent at each stop. When you

get home, you pat yourself on the back for a job well done because you

still have 50 L.E left in your wallet.

We do something similar with communication links, called creating

"a link budget" The traveller is the signal and instead of money it starts

out with ”power".


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It spends its power (or attenuates, in engineering terminology) as it

travels wired or wireless.

So you can use a credit card along the way for extra money infusion,

the signal can get "margin" extra power infusion along the way from

intermediate amplifiers such as microwave repeaters foe telephone links

or from satellite transponders for satellite links. The designer hopes that

the signal will complete its trip with just enough power to be decoded at

the receiver with the desired signal quality.

In our example, we started our trip with 1000 LE because we wanted

a budget vacation. But what if our goal was a first-class vacation with

stays at five stars hotels, best shows and travel by A1000LE budget

would not be enough and possibly we will need instead $5000. The

quality of the trip desired determines how much money we need to take

along.

Link budget means to catalog all losses and gains between the two

ends of communication i.e. mobile station (MS) and eNodeB to yield the

maximum allowable (or available or acceptable) loss in signal strength

that can be tolerated between the transmitter and receiver. Link budget

traces power expenditures along path from transmitter to receiver to

identify or determine the maximum allowable path loss and to determine

the maximum feasible cell radius using propagation model.

Link budget is defined sometimes as the difference between

transmitter effective isotropic radiated power (EIRP) and the minimum

signal strength at the receiver i.e. the receiver sensitivity for acceptable

quality .Link budget is specified in logarithmic units (decibels) .Link

budget output is fed to propagation model to provide the greatest spatial


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distance between transmitter and receiver at which reliable

communication of the desired quality can still take place.

3.4 Why we use Link Budget?

link budget is necessary to determine or calculate the maximum

allowable or available, or accepted path loss (MAPL) where

communication is achieved reliably or that will provides adequate signal

strength at the cell boundary for acceptable voice quality over 90% of the

coverage area if it is flat or 75% if it is hilly .Link budget is necessary to

determine the radius of the cells, and finally to determine the locations of

cell sites as well as the spacing between them to ensure reliable and

uninterrupted communication as mobile stations (MSs) move through the

coverage area of interest.

3.5 What are the types of link budget?

Since communication in mobile cellular phone system between mobile

stations (MSs) and eNodeB is bidirectional. Thus it depends on the

quality of the both reverse link and forward link. There are two link

budgets:

Reverse link budget (up link budget) i.e. as signal is transmitted

from mobile station (MS) and received by eNodeB.

Forward link budget (down link budget) i.e. as signal is transmitted

from eNodeB and received by mobile station (MS).

The reverse link budget has to be considered in system design first then

forward link budget and finally link balance will be made. But since

coverage is usually reverse link limited, we will focus on reverse link

budget (up link budget).


3 - 8

3.6 Up link Budget (uplink coverage)

Most mobile telephony systems are frequently limited by the

uplink, so it is useful to start link budget calculations with the uplink

coverage requirements.

The calculations are performed according to the following stages:

User equipment (UE) effective isotropic radiated or transmitted

power per physical resource block (PRB)

The uplink required bit rate per physical resource Block (PRB)

(Rrequired, PRB)

The uplink required SINR ( ) given the uplink required bit rate

physical resource Block (PRB) (Rrequired, PRB).

ENodeB receiver sensitivity (SeNodeB)

Uplink noise rise or interference margin (IM) (BIUL)

Log normal fading margin (BLNF)

Uplink link budget maximum allowable path loss (MAPLUL)

3.7 Up Link Budget Entries:

The following set of definitions is to be read in conjunction with the

appended reverse link budget (uplink budget) spread sheet.

3.7.1 Maximum mobile station (MS) transmitted power per traffic

channel:

It is the power coming out of the radio / amplifier and into the

antenna power; the power value is 23 dBm at cellular frequencies .These

values are taken from minimum performance standards for a 200

milliwatt mobile station.


3 - 9

3.7.2 Mobile station (MS) transmitter antenna gain (dBi) :

An antenna is a device used to transmit or receive radio frequency

(RF). The radio produces an RF signal and the antenna is the transport

medium used to direct that signal onto free space for its eventual

reception by another antenna attached to a receiver. One of the most

important aspects of an antenna is the antenna gain.

Mobile station (MS) antenna gain is the measure of strength of the

amplification effect of MS antenna directed signal with respect to signal

loss. It is the output transmitted power from the mobile station, in a

particular direction, compared to that produced in any direction by a

perfect reference antenna (isotropic antenna or dipole antenna).

An antenna can create an amplification effect depending on its

construction. The amplification effect is the result of focusing the

transmission signal into a tight beam. Antenna gain works by the same

principle. Signal loss simply describes a decrease in signal strength. Gain

and loss are very important to antenna and radio performance because

they directly affect signal quality and the signal transmission and

reception capabilities. Antenna gain has a direct effect on the total power

radiated from an antenna. The value of the power transmitted into an

antenna will not leave the antenna at the same value. It will be increased

by the amount of gain of the antenna.

Antenna gain can be expressed in dBi, decibels relative to an idea

isotropic radiator or dBd, decibels relative to an idea dipole effective

area. A half –wave dipole antenna has an isotropic gain of 2.15 dBi. This

means that the dipole, in the direction of maximum radiation, is 2.15dB

more intense than that of an isotropic radiator, based on the same input

power.


3 - 10

The value taken for MS antenna gain ranges between 0 dB this is the

gain of the mobile station (MS) antenna. At both cellular and personal

communication system (PCS) frequencies, this is a dipole whose gain can

be taken to be 2.2 dBi.

Mobile station (MS) antenna gain is defined either absolute gain or

relative gain.

The absolute gain: it is the ratio of maximum radiation intensity in

(watts) per unit solid angle to the total input power over 4 .

The relative power antenna gain

It is the power gain of the antenna concerned in certain direction to

the power gain of a reference antenna assuming the input power is the

same for each antenna. The reference antenna may be isotropic antenna or

dipole antenna. The isotropic antenna radiates equally in all directions in

all planes like point of source. It is fictions or hypothetical antenna and is

used as a reference.

3.7.3 Head /Body Losses (dB)

Head /body loss refers to the attenuation of the radio signal during

both transmission and reception as the mobile station antenna is held to

the ear of the mobile station (MS). At personal communication system

(PCS) and cellular frequencies, this attenuation is mainly due to the head

of the user while at lower frequencies (large wave lengths) the entire

human body could distort the radiation pattern of the mobile station

antenna. Head/body losses are the amount of power that is absorbed

through the head and body of the human being from MS.

Typically head /body loss values range from 2 to 5 dB (3dB).Values

to be used in the link budget are typically provided by the wireless

network operator based on field measurements or prior experience. It is


3 - 10






relative gain.























3 - 10






relative gain.























3 - 11

important to obtain these values from the operator since any design loss

raises design cell count.

It worth to mention that in fixed wireless local loop (FWLL), the

head /body loss is zero while in mobile cellular mobile has a value.

3.7.4 Physical resource block:


occupies one OFDM or OFDMA symbol in the time domain and one

subcarrier in the frequency domain.

A transmitted OFDMA signal can be carried by a number of parallel

subcarriers.

Each LTE subcarrier is 15 kHz. Twelve subcarriers (180 kHz) are

grouped into a resource block. Depending on the carrier bandwidth, LTE

supports a varying number of resource blocks. The downlink has an

unused central subcarrier.

The following illustration shows resource block definition:

Figure (3-2) Resource Block Definition in Frequency Domain.

A resource block is limited in both the frequency and time domains.

One resource block is 12 subcarriers during one slot (0.5 ms).


3 - 11










subcarriers.










3 - 11










subcarriers.










3 - 12

In the downlink, the time-frequency plane of OFDMA structure is used to

its full potential. The scheduler can allocate resource blocks anywhere,

even non-contiguously.

A variant used in the uplink requires the scheduled bandwidth to be

contiguous and a single carrier. The method, called SC-FDMA, can be

considered a separate multiple access method.

A user is scheduled every Transmit Time Interval (TTI) of 1 ms,

indicating a minimum of two consecutive resource blocks in time at every

scheduling instance. The minimum scheduling in the frequency

dimension is the width of one resource block. The scheduler is free to

schedule users both in the frequency and time domain.

The illustration in shows user scheduling in the time and frequency

domain for downlink and uplink:

Figure (3-3) Downlink and Uplink User Scheduling in Time and

Frequency Domain.


3 - 12















Frequency Domain.


3 - 12















Frequency Domain.


3 - 13

The bit rate requirement should be based on the service for which the

system is dimensioned, and as a compromise between conflicting needs

and trends, with the following considerations:

With a small 'PRBn the required bit rate can be satisfied with a minimum

of resources. This leaves a maximum amount of space in the time-

frequency resource plane for other users to maximize capacity.

At a large 'PRBn , the transmitted blocks are spread over a frequency

interval, with less power used per physical resource block. A lower

modulation scheme and/or a higher coding rate can be selected. The

receiver is capable of decoding the transmissions at lower SINR, to give a

higher path loss leading to an increased cell range. Additionally, the user

equipment can reduce maximum output power when using large 'PRBn

according to the 3GPP document user equipment (UE) radio transmission

and reception. The back-off allowed is not assumed to be used at cell

edge.

The impact from noise rise on the resulting coverage range when

varying 'PRBn in the dimensioning plays a comparatively minor role, unless

the noise rise is very high.

All physical resource blocks must be consecutive in the uplink.

Large 'PRBn may be less probable if the scheduler operates efficiently.

Using a few different values of for calculating the link budget can be

helpful.

3.7.5 User equipment effective isotropic radiated power (EIRP) per

physical resource Block (PRB)

All allocated resource blocks share the total user equipment output

power.


3 - 14

Assuming that all resource blocks are allocated an equal amount of

power, the power per physical resource block (PRB )is calculated in the

following way:

Equation (3-1) represents power of user equipment per physical

resource block

Equation (3-2) represents Effective Isotropic Radiated Power of user

equipment

Where:

GUE is the user equipment transmitting antenna gain [dBi]

LHBL is the head body loss [dB ]

Gother is the gain due to using MIMO.

LHBL is head/ body loss [dB]

EIRP means effective or equivalent isotropic radiated power. This

refers to the effective isotropically radiated power from the mobile station

(MS) at the antenna connector or it is the power radiated within a given

geographical. It is the effective input power to hypothetically isotropic

antenna that achieves the maximum radiated intensity in any direction. It

is a function of the MS transmitted power and the MS transmitter antenna

gain and head/body losses.

3.7.6 eNodeB receiver thermal noise density No

This simply refers to the thermal noise floor at absolute temperature.

No is eNodeB thermal noise density and given by:

No = 10log KT


3 - 14



following way:


resource block


equipment

Where:















No = 10log KT


3 - 14



following way:


resource block


equipment

Where:















No = 10log KT


3 - 15

Where:

K is Boltzman constant = 1.3806488 × 10-23 Watt/Hertz/Kelvin or

joule /Kelvin (J/K)

T is temperature in kelvin degree =290 degree Kelvin or degree

Celsius (K) =273+17 degree centigrade

No =10 log (1.3806488 × 10-23 *290) / 1 mW = -174 dBm/Hz

Equation (3-3) represents eNodeB receiver thermal noise density

3.7.7 eNodeB receiver noise figure (NF) (dB)

The eNodeB receiver noise figure (NF) is a measure of the signal to

noise ratio (SNR) degradation when signal enters receiver till SNRi reach

the input of demodulator by the eNodeB front end RF amplifier and filter

Noise figure is given by:

NF=10 log (SNRi / SNRo)

Equation (3-4) eNodeB receiver noise figure.

Where:

SNR: It is the input signal to noise ratio. SNRo is the output signal to

noise ratio.

3.7.8 The uplink required bit rate per physical resource Block (PRB)

(Rbrequired, PRB,UL)

Dimensioning starts by defining the quality requirement. Quality is

expressed as a certain bit rate that can be provided to one individual user

at the cell edge with a certain probability. The required bit rate follows

the service for which the system is dimensioned.

All calculations are performed per physical resource block. Table (3-1)

shows how to obtain the required bit rate per physical resource block; the

required bit rate is divided by the number of physical resource blocks 'PRBn


3 - 16

that can be allocated to obtain that bit rate. The required bit rate per

resource block is given by:

Equation (3-5) represents the required bit rate per physical resource

block

Where:

: Required bit rate

: Physical resource block

In a real system, 'PRBn is selected by the scheduler on a 1 ms Time

Transmission Interval (TTI) level. In a dimensioning exercise, the

number 'PRBn can be selected freely, guided by experience and

understanding of the system within the constraints of total deployed

bandwidth, as shown in table (3-1).

Table (3-1) bandwidths and number of physical resource blocks (PRB)

specified in 3GPP

3.7.9 The uplink required SINR ( ) given the uplink required bit

rate Rrequired, PRB


3 - 16




block

Where:

: Required bit rate








specified in 3GPP


rate Rrequired, PRB


3 - 16




block

Where:

: Required bit rate








specified in 3GPP


rate Rrequired, PRB


3 - 17

Similar to High Speed Packet Access (HSPA) in WCDMA, LTE

includes a variety of different transport formats with different modulation

and coding schemes. Each format has a specified bit rate. The SINR

requirement for decoding a particular transport format has been

determined by a large set of simulations. The simulation results in a set of

tables for different channel models and for different antenna

arrangements. As an approximation, the simulation results have been

fitted to a semi-empirical parameterized expression. The expression for

the dependency between Rrequired,PRB and the SINR is expressed along

with the semi-empirical constants a0, a1, a2 and a3.

Using the required bit rate Rrequired,PRB , a SINR is obtained that

represents the requirement on signal quality.

For the transport formats in LTE, given the required bit rate per resource

block, RPRB, the signal-to-interference-and-noise ratio (SINR), γ, is

determined by a set of link simulations.

The uplink cases simulated include the following:

Antenna techniques: 2-branch RX diversity

Modulation schemes: QPSK, 16-QAM

Channel models and Doppler frequency EPA 5 Hz, EVA 70

Hz, ETU 300Hz

Performance analysis of multipath propagation channels:

The multipath propagation condition consists of several parts:

A delay profile in the form of a ―tapped delay-line‖, characterized

by a number of tapes at fixed positions on a sampling grid. The

profile can be further characterized by the r.m.s delay spread and

the maximum delay spanned by the taps.


3 - 18

A combination of channel model parameters that include the Delay

profile and Doppler spectrum that characterized by a classical

spectrum shape and a maximum Doppler frequency.

Both delay profiles and Doppler spectrum for various E-UTRA

channel models were considered. The delay profiles are selected to be

representative of low, medium and high delay spread environments. The

resulting model parameters.

Here the Excess tap delay and Relative power were analysed and the

mobile radio channels such as Extended Pedestrian A, Extended

Vehicular A, Extended typical urban Model and HSTC model

performance were compared using the Table (3-2).Model No. of channels taps Max. Delay

Extended Pedestrian A

(EPA)7 410 ns

Extended Vehicular A(EVA) 9 2510ns

Extended typical urban(ETU) 9 5000ns

Table (3-2) Channel models specifications

Table (3-3) Channel model specifications

EPA EVA

Excess tab delay(ns) Relative power

(dB)

Excess tab

delay(ns)

Relative power (dB)

0 0 0 0

30 -1 -30 -1.5

70 -2 150 -1.4

90 -3 310 -3.6

110 -8 370 -0.6

190 -17.2 710 -9.1

410 -20.8 1090 -7


3 - 19

Extended urban and HSTC modelETU HSTC model

Excess tap delay (ns) Excess tap delay (ns) Excess tap delay (ns) Excess tap delay (ns)

0 -1 0 -1

50 -1 900 -21

120 -1 1900 -35

200 0 2200 -39

230 0 2700 -39.1

500 0 6100 -43

1600 -3 7100 -21.2

2300 -5 10100 -35

5000 -7 - -

Table (3-4) channel propagation conditions

Table (3-4) shows channel propagation conditions that are used for

the performance measurements in multi-path fading environment for low,

medium and high Doppler frequencies. In this paper, the combination of

channel models that include the Delay profile and the Doppler spectrum

are considered for the simulation [5].Model Maximum Doppler frequency

EPA 5 Hz

EVA 70 Hz

ETU 300 Hz

HSTC 1340 Hz

Table (3-5) Maximum Doppler frequency channel model

Table (4&5) shows multi-path delay profiles that are used for the

performance measurements in multi-path fading environment. The Excess

tap delay functions can be expressed in terms of Doppler spectrum as

mentioned below.

S (f) ∝1/((1-(f/fd)2)0.5

Equation (3-6) represents Doppler spectrum


3 - 20

Where:

S (f): Doppler spectrum,

f: Frequency,

fd: It is the Doppler frequency which proportional inversely with Doppler

spectrum.

1- Extended Pedestrian A (EPA)

Extended Pedestrian A. A propagation channel model based on the

International Telecommunication Union (ITU) Pedestrian A model,

extended to a wider bandwidth of 20 MHz.

The pedestrian channel model represents a UE speed of 3 km/h. It

described by

Tau: is a vector of path delays, each specified in nano seconds.

Tau: [0 30 70 90 110 190 410]/109

PDB (Power Delayed Bus): is a vector of relative path powers, in dB

PDB = [0 -1 -2 -3 -8 -17.2 -20.8]

2- Extended Vehicular A (EVA)

• Extended Vehicular A. A propagation channel model based on the

International Telecommunication Union (ITU) Vehicular A model,

extended to a wider bandwidth of 20 MHz.

• The vehicular channel model represents UE speeds of 30, 120 km/h and

higher.

Tau= [0 30 150 310 370 710 1090 1730 2510]/ (109).

PDB= [0 -1.5 -1.4 -3.6 -0.6 -9.1 -7 -12 -16.9].

3-Extended Terrestrial Urban (ETU)

A propagation channel model based on the GSM Typical Urban model,

extended to a wider bandwidth of 20 MHz It models a scattering

environment which is considered to be typical in a urban area.


3 - 21

Tau= [0 50 120 200 230 500 1600 2300 5000]/(10^9)

PDB=[-1 -1 -1 0 0 0 -3 -5 -7]

3.7.10 the required signal-to-interference-and-noise ratio SINR ett arg

given the required bit rate RPRB

The results, including an implementation margin, have been fitted to

a semi-empirical parameterized expression for the required signal-to-

interference-and-noise ratio SINR ett arg given the required bit rate RPRB is

written as follows:

Equation (3-7) represents the required signal-to-interference-and-noise

ratio SINR.

The semi-empirical parameters for uplink a0, a1,a2 and a3 are given in

tables (3.6)

Table (3- 6) semi-empirical parameters for uplink

3.7.11 eNodeB receiver sensitivity (SeNodeB)

eNodeB receiver sensitivity SeNodeB is the required signal power at

the system reference point when there is no interference contribution

from other user equipments. The following relation describes eNodeB

receiver sensitivity per physical resource block (PRB):


3 - 21

Tau= [0 50 120 200 230 500 1600 2300 5000]/(10^9)

PDB=[-1 -1 -1 0 0 0 -3 -5 -7]






written as follows:


ratio SINR.


tables (3.6)








3 - 21

Tau= [0 50 120 200 230 500 1600 2300 5000]/(10^9)

PDB=[-1 -1 -1 0 0 0 -3 -5 -7]






written as follows:


ratio SINR.


tables (3.6)








3 - 22

Equation (3-8) represents eNodeB receiver sensitivity

Where

Nt is the thermal noise power density and is equal -174 dBm/Hz

NfeNodeB is the noise figure of the eNodeB receiver [dB]

WPRB is the bandwidth per physical resource block (PRB): 180 kHz

ULett ,arg is SINR requirement for the uplink traffic channel [dB]

ULPRBN , is the thermal noise per physical resource block in uplink is

given by:

Equation (3-9) represents the thermal noise per physical resource

block in uplink

The eNodeB receiver can be assumed to have a noise figure of 2 dB with

tower mounted amplifier (TMA) and 3 dB without.

3.7.12 Up link noise rise or interference margin (IM) BIUL :

In LTE a user does not interfere with other users in the cell since

they are separated in the frequency/time domain. The noise rise in the

uplink depends only on interference from adjacent cells. In the link

budget, an interference margin compensates for noise rise. The standard

case of closed loop power control is shown as a linear ratio. The uplink

interference margin is given by:

Equation (3-10) represents Up link noise rise or interference margin.

Where:


3 - 22


Where






given by:


block in uplink











Where:


3 - 22


Where






given by:


block in uplink











Where:


3 - 23

ULett arg is the SINR target for the uplink open loop power control.

ULQ is average uplink system load.

CLF is defined as the ratio of actual capacity to pole point capacity.

Pole point capacity is defined as the capacity when all user equipment

raise their power to infinity this is a hypothetical situation which is taken

as a reference.

F is the average ratio of path gains for interfering cells to those of the

serving cell.

F is defined and investigated thoroughly for WCDMA radio network

dimensioning. Table (3.7) gives values for F at varying electric tilt with

30 meter antenna height and 3-sector sites. The values are based on

system simulations.

Table (3.7) examples of F for varying tilt

3.7.13 Log normal fading margin:

Fading is defined as the random variation (change or fluctuation) of

the received signal. There are different types of fading: large scale or

slow fading and small scale or fast fading.

Fading is described using probability density functions: large scale or

slow fading is log normal distributed while small scale or fast fading

which is Rayleigh or Rican distributed. Rayleigh distribution describes


3 - 24

the received signal is due to only reflection and there is no line of sight

(LOS). Log normal distribution describes signal changes due to

abstraction in the path between eNodeB and mobile station (MS).

Fading margin is an extra margin is included in the link budget. The

lognormal fade margin is calculated based on the coverage objective,

which is typically specified as a target coverage probability at cell edge.

Typical numbers are 90% and 75% edge coverage probability. Achieving

90% edge coverage implies that at 90% of the locations at edge, a cell can

be initiated and kept up.

Using path loss models, one can relate area coverage probability to

edge coverage probability and hence to fade margin requirement. 95%

area coverage probability is mapped to 75% edge coverage. These values

presume a completely noise limited receiver.

The lognormal (or slow fading) margin models the required area

coverage probability. By adding this margin, a probability is secured for

setting up and maintaining a connection at a given quality.

Table (3.8) shows fading margins in dB for varying standard deviation σ

of the lognormal fading process and different coverage probabilities:

Table (3.8) log normal fading margins for varying standard deviation of

lognormal Fading


3 - 25

Equation (3-11) represents Log normal fading margin

Where:

is the mean of log normal.

is the standard deviation of log normal.

P% is the coverage probability

The standard components are given for link analysis in the radio

interface. The standard margins for indoor, car penetration loss, body

loss, feeder loss, jumper loss, and antenna gain are the same as any

mobile network. A fading margin is required to guarantee a certain

coverage probability. MAPLUL represents the maximum allowable path

loss in uplink link budget, fed into the downlink link budget.

3.7.14 eNodeB receiver cable feeder, jumper and connector losses

Feeder cable loss

Feeder cable loss is the loss of electrical energy due to the inherent

characteristics of the feeder cable. The eNodeB receiver feeder cable is

dependent on the feeder type and length of feeder run. The receiver cable

and connector losses are nominally taken in the range of 2 dB to 4 dB.

When the cable length and diameter (and hence attenuation/feet) are

known, the actual cable losses may be substituted in the link budget along

with additional margin of 0.5 dB for connector (and duplexer) losses.

Radio equipment should be placed as close as possible to the antennas in

order to reduce the feeder cable loss.

Typically feeder cable diameters used are 7/8" and 15/8" and

corresponding attenuations are 6.15 dB/100 meters and 3.84 dB/meters.

Jumper loss "Lj"


3 - 25


Where:











Feeder cable loss












Jumper loss "Lj"


3 - 25


Where:











Feeder cable loss












Jumper loss "Lj"


3 - 26

Jumper loss is the loss of electrical energy due to the connection of

the tower top amplifier with the antenna using jumpers. A typical value of

the jumper is 11.2 dB/100m.When the used jumper type and length is

known, the total jumper loss can be calculated.

Connector loss "Lc"

It is the loss of electrical energy because of connectors that make the

antennas tied with the top of the tower. A typical value of the connector

loss is 1 dB.

3.7.15 Building / vehicle penetration loss:

This refers to the attenuation of the signal as it passes through one or

more walls of the building in the desired coverage area. When a mobile

station (MS) is used inside the building and the eNodeB is situated

outside, there is a loss when the signal penetrates the building. It is

defined as the difference between the average signal strength outside the

buildings and the average signal strength over the ground floor of the

building. The value of penetration loss must be included when designing

link budget. Table (3.9) shows the value of penetration loss on different

morphology classesIn building dense

urban

In building

suburban

In building rural In car

20 18 12 9

Table (3-9) values of penetration loss on different morphology classes

When the MS is situated in a car without external antenna, an extra

margin has to be added to cope with the penetration loss of the car. This

extra margin is typically 9 dB.


3 - 27

3.7.16 eNodeB receiver antenna gain (dBi)

This refers to the gain of the receiving antenna at eNobeB .While the

actual antennas used in the network may vary from site to site, a nominal,

representative value is provided in the link budget based on the frequency

of operation and sectorization.

The nominal antenna gain values for personal communication

systems (PCS) and cellular frequencies differ based on the cell Omni or

sectorized .The gain units are dBi or gain with respect to an isotropic

radiator. The value of antenna gain also can be varied depending to the

manufacturer. Typically a value of eNondeB receiver antenna gain is

typically 12 dBi for omni cell and 18 dBi for sectorized cell

3.7.17 Uplink link budget maximum allowable path loss (MAPLUL)

Finally, the uplink link budget maximum allowable path loss

(MAPLUL) Can be calculated as follows:

Equation (3-12) represents Uplink link budget maximum allowable

path loss.

Where: (MAPLUL) is the maximum allowable path loss due to

propagation in the air [dB]

BLNF is the log-normal fading margin [dB]

BIUL is the uplink interference margin [dB]

LCPL is the car penetration loss [dB]

LBPL is the building penetration loss [dB]

GeNodeB is the eNodeB receiver antenna gain [dBi]

Gother is the other gain [dBi]

Lf is eNode B feeder loss [ dB ]


3 - 27
















path loss.











3 - 27
















path loss.











3 - 28

Lj is the Jumper loss [dB]

LC is connector loss [ dB ]

3.8 Morphologies classifications

Dense urban (DU):

Central business districts with skyscrapers or with buildings with having

10 to 20 stories and above, the building separation (S) less than 10

meters. Clutter height higher than 30 meters.

Urban (UR):

Residential , office area, hotels, hospitals etc with buildings having 5 to

10 stories and street width less than 5 meters and building separation (S)

less than 10 meters. Clutter height higher from 15 to 30 meters.

Suburban(SU):

Mix of residential and business communications with 2 to 5 stories shops

and offices. The building separation is (S) less than 20 meters. Villages or

high ways scattered with trees and houses, some obstacles near the MS

but not very congested.

Rural area:

Parks or fields with small trees with height less than 12 meters and 20%

house density of residential area of 2 stories with wide roads, The

building separation is (S) less than 20 meters. Clutter height higher than

3o meters.

Open areas:

Clutter height higher than 3 meters open areas, parks, fields, paved areas.

Morphology

class

Clutter height

(meters)

Building

separation

(meters)

Morphology definition

Dense urban H>30 S<10 Building height more than 10 stories


3 - 29

Urban 15<H<30 S<10Building height between 5 to 10 stories and

street width <5 meters

Suburban 10<H<15 S<10 Residential or office areas of 3-4 stories

Rural H<10 S<20

Residential areas of 2 stories with wide roads,

parks or fields with small trees<12meters and

20% house density

Open H<3 S<20 Open areas, parks, fields, paved areas

Table (3-10) summarizes the features of different morphologies.

3.9 Downlink Budget

The downlink link budget is calculated for the following purposes:

• To determine the limiting link

• To determine the bit rate that can be supported in the downlink at the

uplink cell range limit.

The calculations are performed according to the following steps:

• Path loss from uplink

• Bit rate requirement

• Power per resource block

• Downlink noise rise (interference margin)

• Downlink link budget

• Receiver sensitivity, UE

• Bit rate at the cell edge

• Concluding the link budge

3.9.1 Path loss from Uplink

(MAPLUL) from the uplink link budget calculations is the starting

point of the downlink calculations and is used to obtain a downlink noise

rise estimate. At the end of the link budget calculation process, if the

downlink (MAPLUL) is less than the uplink (MAPLUL), both the uplink


3 - 30

and downlink link budgets can be recalculated (including the noise rise)

using the new (MAPLUL).

3.9.2 Bit Rate Requirement

If the bit rate requirement is not expressed per resource block, it is

divided by (Rreq) to obtain (Rreq). As with the uplink, the bit rate

requirement is expressed per resource block in the calculations. However,

unlike the uplink, the downlink scheduler can allocate resource blocks

across the entire deployed bandwidth without requiring them to be

consecutive. It can be shown that it is always favourable to spread the

transmission across as many resource blocks as possible. Assuming this,

the number of allocated

3.9.3 The down link required bit rate (Rb required, PRB,DL ) per physical

resource block (PRB)

If the down link bit rate requirement Rb, required,DL is not expressed per

physical resource block (PRB), it is divided by nPRB to obtain

Rbrequired,PRB,DL .

As with the uplink, the bit rate requirement is expressed per physical

resource block in the calculations. However, unlike the uplink, the

downlink scheduler can allocate physical resource blocks across the

entire deployed bandwidth without requiring them to be consecutive.

It can be shown that it is always favourable to spread the transmission

across as many physical resource blocks (PRB) as possible. Assuming

this, the number of allocated physical resource blocks nPRB in the

downlink for dimensioning is set to the total number of physical resource

blocks for the deployed bandwidth.


3 - 31

In this process, the obtained bit rate requirement per physical resource

block is not used directly to calculate power per physical resource block,

but to compare with the rate that can be obtained at the cell edge given by

the uplink link budget. Alternatively, it can be used as a starting point for

link budget calculations.

3.9.4 eNodeB radiated or transmitted power (EIRP) per physical


The power in LTE is shared by all physical resource blocks. It is

assumed that all physical resource blocks are allocated an equal amount

of power. An individual physical resource block has no power control.

Instead, users are scheduled with high rates every millisecond. The e

Node B transmitted or radiated power per physical resource block is:

Equation (3-13) represents eNodeB transmitted power (EIRP) per

physical resource block (PRB).

Where:

Pnorm,ref : is the sum of nominal power from all radio units in the cell at

the reference point [W]. This means if MIMO is used with two radio

units of 20 W each, is equal to 40W.It is expected that 20 W, 40 W and

60 W power classes will be common. The nominal power at the reference

point can be reduced by loss in feeders.

nRB : is physical resource block.

3.9.5 Thermal noise per physical resource block in the downlink

(N PRB,DL )

N PRB,DL is the thermal noise per physical resource block in the downlink,

defined as follows:


3 - 31















Where:








(N PRB,DL )


defined as follows:


3 - 31















Where:








(N PRB,DL )


defined as follows:


3 - 32

Equation (3-13) represents Thermal noise per physical resource

block in the downlink

NfUE The assumed noise figure Nf for typical user equipment (UE)

receiver is 7 dB.

3.9. 6 the down link noise rise or interference margin (IM) (BIDL)

The down link noise rise on the cell edge is needed for the link

budget and is calculated using the following expression where all

quantities linear:

Equation (3-14) represents the down link noise rise or interference

margin

Where:

DLQ : is the downlink system load.

FC : is the average ratio between the received power from other cells to

that of own cell at cell edge locations.

The load is modeled with QDL. The link budget must be true for a network

with a given load. Normally, one design input is to determine the load for

which the coverage is available.

The cell plan quality is modeled with the factor FC . FC describes the

ratio of received power from all other cells to that received from own cell

at a location near the cell edge. Table (3-11) gives values at varying

electric tilt with 30 meter antenna height, and 3-sector sites. The values


3 - 32




receiver is 7 dB.




quantities linear:


margin

Where:












3 - 32




receiver is 7 dB.




quantities linear:


margin

Where:












3 - 33

are based on system simulations. For dimensioning other antenna heights,

see appendix (A)

Table (3-11) examples of Fc at cell edge for varying tilt

3.9.7 The calculated down link SINR on the cell edge

The downlink calculated SINR on the edge of a cell with the size

given by MAPLUL is given by the following equation:

Equation (3-15) represents down link SINR on the cell edge.

3.9.8 The down link calculated bit rate Rcalculated at cell edge

The cell edge down link SINR estimate or calculated is transformed

into a calculated bit rate per physical resource block, Rbcalculated,PRB by the

same type of semi-empirical relationship as for the uplink SINR

requirement . For the downlink, the semi-empirical constants or

parameters a0, a1,a2 and a3 are given in table (3-12) .


3 - 33


see appendix (A)













3 - 33


see appendix (A)













3 - 34

Table (3-12) Semi-empirical parameters for down link

The downlink cases simulated include the following:

Antenna techniques: SIMO 1x2, TX diversity 2x2, Open loop

Spatial Multiplexing (OLSM) 2x2

Modulation schemes: QPSK, 16-QAM, 64-QAM

Channel models and Doppler frequency: extended pedestrian

model A (EPA) 5 Hz, extended vehicular model A (EVA) 70 Hz,

extended terrestrial urban model (ETU) 300 Hz

Number of OFDM symbols used for PDCCHs: 1


• Antenna techniques: 2-branch RX diversity

• Modulation schemes: QPSK, 16-QAM

• Channel models and Doppler frequency EPA 5 Hz, EVA 70

Hz, ETU 300Hz

The results, including an implementation margin, have been fitted to a

semi-empirical parameterized expression for bit rate RPRB as follows:

Equation (3-16) represents the down link calculated bit rate Rcalculated

at cell edge.

Where:


3 - 34














Hz, ETU 300Hz




at cell edge.

Where:


3 - 34














Hz, ETU 300Hz




at cell edge.

Where:


3 - 35

a0, a1,a2 and a3 are fitted parameters and the SINR is expressed in dB.


3.9.9 Concluding link budget according to required and calculated

bit rate

The resulting or calculated bit rate is multiplied by the number of

physical resource blocks (PRB) (nPRB) to obtain the maximum calculated

bit rate (Rcalculated) expected on the cell edge. If the uplink is really the

limiting link, (Rcalculated) should be larger than the required bit rate

(Rrequired). If the resulting or calculated bit rate (Rcalculated) is lower than the

required bit rate (Rrequired), then the downlink is the limiting link

3.10 Downlink Limited Link Budget

If the resulting or calculated bit rate (Rcalculated) is lower than the

required bit rate (Rrequired), then the downlink is the limiting link. In that

case, the true maximum cell range must be determined by back tracking

the downlink link budget calculations.

The downlink link budget calculations are performed according to

the following steps:

(1) R PRB, required is transformed into a required SINR .

(2)The required SINR is used to derive user equipment (UE) sensitivity

(SUE) at the cell edge.

(3)The user equipment (UE) sensitivity (SUE) is used in the link budget,

initially with the same noise rise BIDL as before.

3.10.1 User equipment (UE) receiver sensitivity

The user equipment sensitivity SUE is given by:


3 - 35




bit rate






















3 - 35




bit rate






















3 - 36

Equation (3-17) represents User equipment (UE) receiver sensitivity

3.11.2 Downlink budget maximum allowable path loss (MAPLDL)

The down link budget maximum allowable path loss (MAPLDL )is

described by the following equation:

Equation (3-18) represents Downlink budget maximum allowable path

loss.

Where:

PRBeNodeBEIRP , is the effective isotropic radiated or transmitter power

per physical resource block at the system reference point [dBm]

UES is the user equipment (UE) sensitivity [dBm]

(4)New signal attenuation for down link is derived with the following

equation:

Equation (3-19) represents signal attenuation for down link.

(5)The new down link signal attenuation L sa,max,DL is applied in to obtain

a new BIDL

(6)Equation in the above is iterated until L sa,max,DL and BIDL are constant.

(7)The new L sa,max,DL converted to MAPLDL is now used to calculate the

true cell range.

MAPLDL is used as a measure of cell size. It is converted to

geographical distance by a suitable wave propagation model.

A down link limited system means that the uplink quality exceeds the

requirement. If the bit rate on the cell edge for the uplink is needed, the

uplink budget calculations also must be back tracked:


3 - 36






loss.

Where:





equation:



a new BIDL



true cell range.







3 - 36






loss.

Where:





equation:



a new BIDL



true cell range.







3 - 37

(1)L sa,max,DL from the downlink is applied in to obtain the new down link

MAPLDL and a new uplink noise rise (BIUL) is approximated with the

following expression:

Equation (3-20) represents uplink noise rise.

Where:''PRBn is the number of resource blocks allocated to the service responsible

for the interference. n’’PRB may or may not be equal to n’PRB, the number

of resource blocks allocated to the service for which the link budget is

calculated.

H is the average attenuation factor, depends on the site geometry, antenna

pattern, wave propagation exponent, and eNodeB antenna height. H is the

standard average path loss factor used in coverage and capacity

dimensioning value of 0.36 is recommended for dimensioning.

(2)the equation of the uplink budget maximum allowable path loss

(MAPLUL), is solved for the eNodeB sensitivity eNodeBS , and the downlink

DLsaL max,, is inserted.

(3)the equation of receiver sensitivity is solved for the uplink signal-to-

interference-and- noise ratio (SINR) at the cell edge . is converted to a

logarithmic value.

(4)The corresponding calculated bit rate is calcultedbR , determined.

3.11 propagation models

To make a design and plan of cellular mobile phone systems,

accurate propagation characteristics of the environment should be known

especially the path loss. The calculation of path loss is vital for the


3 - 37








calculated.










logarithmic value.







3 - 37








calculated.










logarithmic value.







3 - 38

determination of RF cell coverage of eNodeB placement and in

optimizing it. There are many prediction models that are used to predict

path loss. Although these models differ in their methodologies, all have

the distance between the transmitter and receiver as a parameter i.e. the

path loss is heavily dependent on the distance between the transmitter and

receiver. Other effects also come into play in addition to distance. In the

following subsections, the propagation model will be defined and why it

is necessary. The different types of propagation predict models for

terrestrial wireless communication systems will be presented briefly, and

then an example of each type will be discussed in detail. The focus is

placed on the following models: free space model, Cost 231 Okumara

Hata model and Cost 231 Walfisch Ikegami model. The last two models

are the most widely used software package for cellular system design.

Definition of propagation model:

Propagation model is a model used to determine the maximum range

of the communication system which provides acceptable quality provided

that the maximum allowable or permissible or accepted path loss (MAPL)

is determined as accurately as possible via link budget. In cellular mobile

phone system propagation model is used to calculate the maximum

distance between the mobile station (MS) and the eNodeB at which

reliable communication take place with the desired quality of service. and

to determine the locations of cell site (CSs) and the spacing between the

CSs in order to ensure reliable and uninterrupted communications as the

MS moves through the required coverage area. The propagation models

are necessary and essential because the various propagation effects and

time varying, dynamic and difficult to predict. The signal traveling from

the eNodeB to the mobile station follows many different paths before


3 - 39

arriving at the receiving antenna of the MS. Each individual path affects

the signal causing attenuation, delay and phase shift. In additional, the

motion of the mobile station (MS) nearby scatters such as trucks and

buses may cause Doppler frequency shifts in each received component.

The received signal at the mobile station (MS) is therefore a result of

direct rays, reflected rays and shadowing or any combinations of these

signals. The path loss can be obtained either by field measurements are

time consuming and expensive while the models are simple and efficient

to use.

3.12Classifications of propagation models

Propagation models can be roughly divided into three types: the

empirical, theoretical and semi-empirical models.

3.12.1Empirical propagation models

Empirical models are usually set of equations, the model parameters

are divided from extensive field measurements data. They are accurate

for environments with the same characteristics as those where

measurements were made. The input parameters for empirical models are

usually qualitative and not very specific e.g. dense urban (DU), urban

(UR), Suburban (SU) and rural (RU) areas and so on. One of the main

drawbacks of empirical models is that they cannot be used for different

environment without modifications. The output parameters are basically

range specific. Empirical models examples are Okumara model and Hata

model.

3.12.2 Theoretical propagation models

They are derived physically assuming some ideal conditions for

example over roof top diffractions model is derived using physical optics

assuming uniform heights and spacing of buildings. Theoretical models


3 - 40

examples are Walfisch and Bertoni model, Ikegami model and free space

model.

3.12.3 Semi – empirical propagation models

The parameters of the theoretical models are empirically to fit

measurement data. Semi –empirical models examples are COST 231 –

Walfisch Ikegami model and COST 231 Okumara Hata model.

Free space model

The free space model is physical model because it describes how

signal propagates. The free-space model is based on expanding spherical

wave front as the signal radiates from a point source in space. The

electromagnetic waves in free space diminish as a function of inverse

square of the distance i.e. (1/d^2), where d is the distance between the

transmitter and receiver and in our case the distance between the mobile

station (MS) and eNodeB. It is mostly used in satellite communication

systems where the signal travels through free space.

Assume that the MS antenna and eNodeB antenna are arranged such

that their directions of maximum gain are aligned i.e. the source and load

impedances match the antenna impedances their polarization are matched

and they are separated by a distance.

Okumara model

In 1968, Okumara model is an empirical developed by Yoshihisa

Okumara based upon an extensive series of measurements of the field

strength made in and around Tokyo city by Y. Okumara in VHF and UHF

land mobile radio services at several frequencies in 100 MHz and 3 MHz.

Okumara model is a graphics- based model using numerous of curves.

Okumara model is applied for prediction of maximum allowable path loss

over macro cell, built up areas. It is also successfully applied in other


3 - 41

urban environment (outside Japan) taking urbanization factor, terrain type

correction into account. Okumara model was limited from 1 Km to 100

Km distance.

The frequencies range from 1 m to 10 meters. Okumara model’s

drawback is the results are available in graghical form.

Okumara – Hata model

In 1980, Hata model is an empirical formula derived from

Okumara’s results. The measurements graphs results have been fitted to a

mathematical model by M.Hata.

The Okumara graphs have been approximated by Hata in a set of

formulas. The Hata model is a formula- based for Okumara model and

can be used more effectively. Okumara –Hata model is applied for

prediction of maximum allowable path loss over macro cell, buit – up,

quasi smooth areas but the equations were limited from 1 Km to 20 Km

distance. The frequencies range from 150 to 1500 MHz. The mobile

station antenna height should be between 1m to 10meters. The eNodeB

antenna height ranges 30 to 200meters. Okumara –Hata model is easily

computable.

COST 231 Okumara Hata model

The Cost 231 Okumara –Hata propagation model was and still is

widely used for coverage calculation in microcellular network planning.

In 1999, it was found by the European community collaborative studied

in the areas of science and technology (COST) that Okumara Hata model

underestimates path loss. Okumara Hata model for medium to small cities

i.e. urban area has been extended and modified to correct the situation

and to cover the frequency band from 1500 to 2000 MHz in the COST

231 project. Thus, COST 231 Okumara Hata model is considered semi


3 - 42

empirical model after adjustment to cover the frequency band of 4G

cellular systems for urban personal communication system (PCS)

applications.

The model include terrain information qualitatively by dividing the

prediction area into a series of clutter and terrain categories namely dense

urban, suburban and rural, open, quasi open… etc environments.

Okumara Hata model with related corrections is the most common model

used in designing real systems. Okumara takes urban area as a reference

and apply correction factors for conversion to the other classifications. In

Okumara Hata model, the path loss is function of several parameters such

as frequency, frequency range, height of MS antenna, height of eNodeB

antenna, and building density. This model has been proven to be accurate

and is used by computer simulation planning tools.

For the parameters, there are only certain ranges in which the model

is valid; that hb should only be between 30m to 200m, hm should be

between 1m to 10m, d should be between 1 Km to 20Km.

3.13 Ericsson variant of COST 231 Okumura–Hata Wave

Propagation model

This section describes the wave propagation characteristics. It is not

expected that a channel wider than 5 MHz will have a significant

difference in the ability to compensate for Rayleigh fading.

The equation to calculate the cell radius R in kilometres is as follows:10R

Equation (3-21) represents cell radius

Where:


3 - 43

A is frequency-dependent fixed attenuation value, shown in table

(3.14)

hb is base station or eNodeB antenna height [m]

hm is height of the user equipment (UE) antenna [m]

a (hm) = (1.1 log F- 0.7) hm – (1.56 log F- 0.8)

Equation (3-22) represents a function of user equipment antenna in RU,

UR, and SU

a(hm) is the Mobile station Antenna height correction factor as described

in the Hata Model for Urban Areas.

a(hm)=3.2[log(11.75hm)]2 - 4.97

Equation (3-23) represents a function of user equipment antenna in

DU areas.

Equation (3-24) represents maximum allowable pathloss as a function

of cell radius.

Table (3-13) fixed attenuation A in Ericsson variant COST 231 Okumura-

Hata propagation model


3 - 43


(3.14)



a (hm) = (1.1 log F- 0.7) hm – (1.56 log F- 0.8)


UR, and SU



a(hm)=3.2[log(11.75hm)]2 - 4.97


DU areas.


of cell radius.




3 - 43


(3.14)



a (hm) = (1.1 log F- 0.7) hm – (1.56 log F- 0.8)


UR, and SU



a(hm)=3.2[log(11.75hm)]2 - 4.97


DU areas.


of cell radius.



Chapter Four

Capacity Dimensioning

Chapter 4: Capacity Dimensioning

4 - 2

Chapter four

Capacity Dimensioning4.1 Introduction

Capacity dimensioning obtains input information to the phases

after radio interface dimensioning: transmission link dimensioning and

eNodeB dimensioning.

The method is specified for a certain system load. The dimensioning

method finds the maximum capacity that the target cell can sustain

momentarily, given the system load in the surrounding cells. It is

improbable that all cells in a system are fully loaded at the same time, as

observed in real networks of different technologies.

The evaluation of capacity needs the following two tasks to be

completed:

Being able to estimate the cell throughput corresponding to the settings

used to derive the cell radius

Analyzing the traffic inputs provided by the operator to derive the traffic

demand, which include the number of subscribers (U), the traffic mix

and data about the geographical spread of subscribers in the

deployment area

The target of capacity planning exercise is to get an estimate of the

site count based on the capacity requirements. Capacity requirements are

set forth by the network operators based on their predicted traffic.

Average cell throughput is needed to calculate the capacity-based site

count.

In LTE, the main indicator of capacity is SINR distribution in the

cell. In this project, for the sake of simplicity, LTE access network is

assumed to be limited in capacity by DL.


4 - 3

The purpose of this chapter is to describe the capacity dimensioning for

the LTE network and to explain the methods used and factors impacting

the capacity dimensioning process. This chapter includes several sections.

The first section describes the cell throughput calculations, while the

second part is about traffic demand estimation. Later sections concern

with capacity based site count evaluation.

Capacity Definition

The number of connections that the wireless channel can support without

unduly degrading the data services carried on the channel.

4.2 Uplink Capacity

4.2.1 IT is based on the following calculations:

Signal-to-Interference-and-Noise Ratio (SINR)

Cell throughput

Number of sites required

4.2.2Signal-to-interference-and-noise ratio

The operating mode with power control assumes perfect power

control (PPC) and infinite power dynamics. User equipment is received at

the signal to interference plus noise ratio (SINR) identical to the bit rate

per physical resource block (PRB) is identical to the bit rate

corresponding to the SINR and the number of allocated physical resource

blocks.

By varying the load QUL , the average user throughput does not change

However, the cell throughput and the cell range will change

The most accurate evaluation of cell capacity (throughput under certain

constraints) is given by running simulations. The best solution to derive

cell throughput is direct mapping of SINR distribution obtained from a


4 - 4

simulator into MCS (thus, bit rate) or directly into throughput using

appropriate link level results.

Capacity dimensioning gives an estimate of the resources needed

for supporting a specified offered traffic with a certain level of QoS (e.g.

throughput or blocking probability). Theoretical capacity of the network

is limited by the number of eNodeB’s installed in the network. Cell

capacity in LTE is impacted by several factors, which includes

interference level, packet scheduler implementation and supported

modulation and coding schemes (MCSs).

The SINR values to support each modulation coding scheme (MCS) are

derived from look-up tables that are generated from link level

simulations. As shown in table (4-1) for urban channel model and a fixed

inter-site distance of 1732m in LTE network.

Table (4-1) SINR values corresponding to each modulation coding

scheme (MCS)


4 - 4















scheme (MCS)


4 - 4















scheme (MCS)


4 - 5

The average signal-to-interference-and-noise ratio (SINR) yields a

bit rate. The result is the bit rate per physical resource block. The average

user bit rate is scaled proportionately with the number of Physical

resource blocks corresponding to the deployed bandwidth.

For the transport formats in LTE, the relationship between bit rate

per resource block (RRB) and Signal-to-Interference-and-Noise Ratio

(SINR), γ, is determined by a set of link simulations.

The uplink simulations include the following:

Antenna configuration: 2-branch RX diversity


Channel models: EPA 5 Hz, EVA 70 Hz, ETU 300Hz


semi-empirical parameterized expression as follows:

Equation (4-1) represents the required bit rate

Where:


The semi-empirical parameter a0 represents the maximum obtainable bit

rate in one resource block as shown in table (4-2)

Table (4-2) semi- empirical parameters for up link


4 - 5















Where:






4 - 5















Where:






4 - 6

In the uplink, one or more resource blocks are always allocated at

each band edge to signalling for users in idle mode on the channel

Physical Uplink Control Channel (PUCCH). For this reason, the number

of physical resource blocks in uplink available for calculating capacity

are always reduced by a number value of 4 is recommended for

dimensioning.

The resulting Uplink average user bit rate per cell is:

Ravg,UL =RRB,UL (nRB - nPUCCH)

Equation (4-2) represents Uplink average user bit rate per cell

Average cell Throughput

The Uplink average cell throughput is by the following equation:

Tcell,UL = QUL Ravg,UL

Equation (4-3) represents the uplink average throughput

Where:

The nRB is different and larger than the number of resource blocks

nRB used for uplink coverage dimensioning

QUL: is the uplink system load

Ravg,UL: Average UP Link data rate

The site throughput:

Where the site capacity is a multiple of the cell throughput, which

depends on the number of cells per site (Not considering any hardware

limitation) According to cell type.

If omni cell then the site throughput is given by:

Tsite = Tcell Equation (4-4)

If 3 sector cell, then the site throughput is given by:

Tsite = 3 × Tcell Equation (4-5)


4 - 7

The total throughput or the overall data rate

To determine the traffic demand estimation, the total throughput

or the overall data rate is given by:

Ttotal = U × TU

Equation (4-6) represents the total throughput or the overall data

rate

Where:

U is the number of users in the network

TU is the throughput per user or peak data rate

The number of sites required

Nsite =

Equation (4-7) represents the number of sites required

4.3 Downlink Capacity

The following downlink capacity calculations are performed:

Signal-to-Interference-and-Noise Ratio (SINR)

Cell throughput

The number of sites required.

4.3.1 The maximum signal attenuation Lsa max at the cell border

The maximum allowable path loss from the uplink is used to find the

maximum sustainable bit rate per physical resource block in the

downlink. Lsa max is given by:

Lsa,Max = MAPL + BLNF – (Gue + Gothers) + LPBL + LCPL+ Lf + Lc

Equation (4-8) represents The maximum signal attenuation Lsa max

at the cell border


4 - 8

Where:

MAPLUL is the uplink budget maximum allowable path loss

(MAPL) from coverage calculation.

BLNF : log-normal fading margin

GUE : User equipment transmitting antenna gain [dBi]

Gothers : It is gains due to MIMO

LBPL : Building penetration loss

LCPL : Car penetration loss

LF : Feeder loss

LC : Connector loss

4.3.2 Thermal noise power density per physical resource block in

downlink

N PRB,DL = Nt + Nf + 10 Log (WPRB)

Equation (4-9) represents Thermal noise power density per physical

resource block in downlink.

Where:

Nt: It is thermal noise power density = 10 log10 KT and is equal

-174 dBm/Hz

Nf : noise figure of receiver = 7 d B

W(PRB) : bandwidth per physical resource block = 180 KHz

NPRB,DL : Down Link thermal noise per physical resource block

K : Boltzmann's constant and its value is 1.38* 10-23

T : Temperature and its value is 290 degree Kelvin


4 - 9

4.3.3 The eNodeB transmitted power per physical resource block

Equation (4-10) represents The eNodeB transmitted power per physical

resource block

Where:

Ptx ,eNodeB, PRB is the eNode B transmitted power per physical

resource block at the system reference point

P (norm) : is the sum of normal power from all radio units in the cell

at the reference point

The average down link noise rise or interference margins is

Equation (4-11) represents the average down link noise rise or

interference margins

Where:

• BIDL : Interference margin (IM)

• Ptx,eNodeB,PRB : is the eNodeB transmitted or radiated power per

physical resource block.

• QDL is the average downlink system load.

• Fc is interference factor.

• N PRB,DL :Noise thermal power density, down link , per PRB.


4 - 9



resource block

Where:








Where:








4 - 9



resource block

Where:








Where:








4 - 10

• nPRB is number of physical resource block.

• F is the cell plan quality factor. It describes the ratio of received

power from all other cells to that received from own cell at a

location near the cell edge locations.

• B(IDL) : Down Link interference Margin

4.3.4 Signal-to-Interference-and-Noise Ratio

The downlink capacity is based on the Signal-to-Interference-and-

Noise Ratio (SINR) at the average location within a cell, denoted as a

linear ratio.

The average SINR is expressed in the average noise rise. This is

similar to the interference margin, but the SINR is evaluated at an

average location instead of at the cell edge.

The resulting average downlink signal-to-interference-and-noise

ratio (SINR), is given by the following equation:

Equation (4-12) represents Signal-to-Interference-and-Noise Ratio

in downlink

Where:

• H is the average attenuation factor dependent on site geometry,

antenna pattern, wave propagation exponent,and base station

antenna height.

• H is the standard average path loss factor used in coverage and

capacity dimensioning And for dimensioning H is value of 0.36


4 - 10









linear ratio.







in downlink

Where:



antenna height.




4 - 10









linear ratio.







in downlink

Where:



antenna height.




4 - 11

• The down link bit rate per physical resource block

• The average signal-to-interference-and-noise ratio (converted to

logarithmic)

• yields an average bit rate by way of and is the bit rate per physical

resource block,

• The bit rate per physical resource block, down link RPRB,DL Given

SINR

Equation (4-13) represents the down link bit rate per physical

resource block

For the downlink, the semi-empirical parameters are given in table (4-3)

Table (4-3) Semi- empirical parameters for downlink

4.3.5The down link cell throughput

The average down link user bit rate per cell is scaled

proportionately with the number of physical resource blocks and is given

by:

Ravg,DL = RRB,DL (nRB,DL- nPDCCH)


4 - 11



logarithmic)


resource block,


SINR


resource block






by:



4 - 11



logarithmic)


resource block,


SINR


resource block






by:



4 - 12

Equation (4-14) represents the down link cell throughput

4.3.6 The down link cell throughput is given by:

Tcell,DL = QDl × Ravg,DL

Equation (4-15) represents the down link cell throughput

Where:

• Raverage,DL is average DL data rate

• R PRB,DL is DL data rate per physical resource block.

• n'PRB is the number of physical resource block

• nPDCCH is the number of Physical DL control channels

• QDL is the average down link system load

4.3.7 The total throughput

Ttotal = U × TU Equation (4-16)

Where:

Ttotal: The total throughput

Tsite: The site throughput

4.3.8 The site throughput

Tsite = Tcell (Omni cell ) Equation (4-17)

Tsite = 3 × Tcell ( 3 sector cell ) Equation (4-18)

Where:

Tcell,DL is the DL cell throughput

The number of sites required

Nsite = Equation (4-19)

Nsite: Number of sites required


4 - 13

4.4 Application or service distribution model

A key element in network planning is to estimate the number of users

that each BS may support. To have an idea about the maximum number

of subscribers that a typical BS can serve the information of possible

different traffic types and their parameters are essential. But On the other

hand, mixed application packet data networks are notoriously difficult to

treat with statistical methods for the general case. The traffic engineering

for how the bandwidth is apportioned to the various active connections is

typically left to operator configuration and is not included in the standard.

In this project, different application classes are introduced and the desired

parameters and usage percentage related to each of the applications are

specified. There are five major classes’ services or applications as shown

in table (1) that are:

Multiplayer interactive gaming

VoIP and Video Conference

Streaming Media

Web browsing and instant messeging

Media Content Downloading

To fulfil the required QoS specifications of each application a number of

important parameters must be met. These parameters are: bit error rate,

jitter, latency and minimum throughput. The list above is sorted in a

decreasing delay sensitivity order. The latency sensitivity gives an

allocation priority to the suffering application.

According to the service types, the first application group can be

classified in the VBR services. Since the goal of this project is to decide

the maximum capacity of a typical base station, will we focus on the


4 - 14

minimum reserved data rate of each VBR service and leave the maximum

sustained data rate for more advanced scheduling procedures.

The first application class i.e. Multiplayer Interactive Gaming needs a

minimum reserved data rate of 50 kbps for each user.

The second class belongs to the CBR service type with the average

reserved data rate of 32 kbps for each user.

The Streaming Media application group can be classified into VBR

services with reserved data rate of 64 kbps.

The last two application classes can be considered as best effort (BE)

service type. The web browsing application group can be assigned the

nominal data-rate of the user while the file transfer protocol (FTP) class is

supported with the remaining capacity assigned to each Subscriber that is

available after satisfying other guaranteed service types.

Table (4.5) applications or services distribution model

However, the other important factor for capacity estimation of a typical

base station is the user demands and the trend of each user type. In the


4 - 15

coming sections an application distribution scenario and two important

scales to follow the market trends are presented.

4.4.1 Service Flows

In the previous sections, we have examined the various factors that

influence the overall channel bandwidth. What remains after accounting

for the per-channel and per-packet overhead is the usable channel

bandwidth. This channel size is the relevant quantity for determining the

service capacity consistent with the QoS parameters. The traffic

engineering for how the bandwidth is apportioned to the various active

connections is typically left to operator configuration.

In this section we will illustrate one way in which this could be

accomplished. We begin by reviewing the three basic service types.

In general service flows related to each application can be identified

with two major traffic rate allocation types:

(i)The Reserved Traffic Rate

It is the committed information rate for the flow of the data rate that

is unconditionally dedicated to the flow and therefore can be directly

subtracted from the available user channel size to determine the

remaining capacity.

(ii)The Sustained Traffic rate

It is the peak information rate that the system will permit. Traffic,

submitted by a subscriber station at rates bounded by the minimum and

maximum rates, is dealt with by the base station on a non-guaranteed

basis.


4 - 16

Based on the above traffic rate allocation methods three service

flows can be defined. These services are as follows:

4.4.2 Constant Bit Rate (CBR) Services

System can support Constant Bit Rate (CBR) by configuring

dedicated frequency-time channel grants to specific traffic flows. The

dedicated resources correspond to a constant throughput rate. CBR

service flows are suitable for applications with strict latency and

throughput constraints and that generate a steady stream of fixed size

packets such as VoIP. These service flows can be dynamically set up or

torn down in response to detection by the system of changing traffic

needs.

On the downlink, the base station directly controls the scheduling of

traffic and allocation of the frequency-time channel resources. Dedicating

a portion of the channel bandwidth for CBR flows is therefore a matter of

keeping track of the allocated resources and transporting any available

packets from appropriately classified traffic.

For the uplink the Unsolicited Grant Service (UGS) scheduling

method is used. The base station dedicates a portion of the uplink channel

bandwidth to a Subscriber Station corresponding to one or more service

flows for the duration of the flow. The base station communicates this

assignment to the Subscriber Station in the uplink channel usage maps

that are periodically broadcast out to all stations.

From a capacity standpoint, the key CBR QoS parameter is the

unvarying Maximum Sustained Traffic Rate, which is the committed

information rate for the flow. The maximum rate is unconditionally

dedicated to the flow and therefore can be directly subtracted from the


4 - 17

available user channel size to determine the remaining capacity. The only

overhead associated with CBR flows is the UGS grant overhead, which

increases the size of the uplink channel usage map.

Although the bandwidth is dedicated for a CBR service flow, the

base station scheduler implementation could still elect to temporarily

“borrow” the dedicated bandwidth on the downlink frame if there is no

CBR traffic to send. The scheduler must however issue uplink grants

according to the CBR service flow configuration whether or not the

subscriber station has any traffic to send (the scheduler has no way of

knowing in advance).

CBR service has a maximum reserved traffic rate. This service is

suitable for applications with strict latency and throughput constraints and

those that generate a steady stream of fixed size packets such as VoIP.

4.4.3 Variable Bit Rate (VBR) Services

For applications that have variable traffic throughput demands

systems support Variable Bit Rate (VBR) services. VBR service flows

are suitable for applications that generate fluctuating traffic loads

including compressed streaming video and VoIP with silence

suppression.

On the down link (DL), the base station directly controls the

scheduling of traffic and allocation of the frequency-time channel

resources. Dedicating a portion of the channel bandwidth is therefore a

matter of keeping track of the allocated resources and transporting any

available packets from appropriately classified traffic. The base station


4 - 18

performs this scheduling successively for each TDMA frame that is sent

out for example every 10 ms so that the time varying nature of the VBR

traffic can be supported in real time.

For the uplink (UL), there are several scheduling methods depending

on the QoS requirements for the service flow. For flows with strict real

time access constraints, periodic polling assures that the subscriber station

will have guaranteed channel access up to a specified Minimum Reserved

Traffic Rate. Real time Polling Service (rtPS) operates by having the

base station poll individual subscriber stations periodically for example

every frame to solicit bandwidth requests. Extended real time Polling

Service (ertPS) operates more like UGS except that the committed

maximum rate can be changed on the fly as controlled by subscriber

station signalling.

For flows with looser real time access constraints, non real time

Polling Service (nrtPS) operates like rtPS except the polls can be

directed at individual or groups of subscriber stations, and the latency of

the base station response to bandwidth requests is not guaranteed. The

subscriber stations can also use piggyback methods to request continuing

channel access.


4 - 19

Table (4.6) mobile service flows and QoS parameters

For capacity calculations, the two key VBR QoS parameters are the

Minimum Reserved Traffic Rate and the Maximum Sustained Traffic

Rate. For VBR, the minimum rate corresponds to the committed

information rate. Since the minimum rate is guaranteed, it can be directly

subtracted from the available user channel size to determine the

remaining capacity. The maximum rate is the peak information rate that

the system will permit. Traffic, submitted by a subscriber station at rates

bounded by the minimum and maximum rates, is dealt with by the base

station on a non-guaranteed basis. The overhead associated with VBR

service comes from the polling method except for ertPS, which basically

has the same overhead as UGS i.e. the size of the uplink channel usage

maps is increased for each active flow.


4 - 20

If the polls are directed at a group of subscriber stations the responses

must use a contention bandwidth request interval to respond since request

collisions can occur.

Although the bandwidth is dedicated for the Minimum Reserved

portion of the VBR service flow, the base station scheduler

implementation could still elect to temporarily “borrow” the dedicated

bandwidth on the downlink frame if there is no traffic to send. The

scheduler must however issue uplink grants for bandwidth requests

according to the VBR service flow configuration for the Minimum

Reserved QoS parameter whether or not the subscriber station has any

traffic to send (the scheduler has no way of knowing in advance).

VBR has a minimum reserved and a maximum sustained traffic

rates. These types of service flows are suitable for applications that

generate fluctuating traffic loads including compressed streaming video.

4.4.4 Best Effort (BE) Services

Best effort (BE) services are intended for service flows with the

loosest QoS requirements in terms of channel access latency and without

guaranteed bandwidth. Best effort services are appropriate for

applications such as web browsing and file transfers that can tolerate

intermittent interruptions and reduced throughput without serious

consequence.

On the downlink, the base station directly controls the scheduling of

traffic and allocation of the frequency-time channel resources. For best

effort services, the affected traffic is sent as surplus capacity that is

available after satisfying other guaranteed service types.


4 - 21

On the uplink, the base station should provide periodic contention

intervals in order for subscriber stations with best effort flows to submit

their bandwidth requests. The subscriber stations can also use piggyback

methods to request continuing channel access.

The overhead associated with best effort services comes from

providing the contention intervals for bandwidth requests.

BE are intended for service flows with the loosest QoS requirements

in terms of channel access latency and without guaranteed bandwidth.

Best effort services are appropriate for applications such as web browsing

and file transfers that can tolerate intermittent interruptions and reduced

throughput without serious consequence. For best effort services, the

affected traffic is sent as surplus capacity that is available after satisfying

other guaranteed service types.

Figure (1) shows a schematic the available bandwidth that is

partitioned

Based on the presented bandwidth partitioning methodology, each of

the desired applications can be assigned with the desired service flow

based on its required quality of service (QoS) parameters. As mentioned

before the realization procedure of this task is not included in the standard

and each vendor must implement it utilizing appropriate traffic

scheduling processes for time and frequency channel recourse allocations.

The scheduling is directly controlled by each Base Station.


4 - 22

4.4.5 Sharing Non-Guaranteed Bandwidth

In comparing best effort services against variable bit rate services an

ambiguity becomes apparent. The system must by definition not admit

more guaranteed bandwidth traffic onto the channel than it can supply.

On the other hand, VBR and BE services can both have non-guaranteed

traffic. For VBR it is the portion of traffic submitted at rates above the

Minimum Reserved rate. For BE it is all of the submitted traffic. How

should the scheduler deal with this situation in cases where there is

insufficient remaining capacity to honor all requests? Shown graphically

in figure (1), what should happen if regions C and D overlap? The answer

is not specified by the 802.16 standard but is left to vendor

implementation.

Figure (4.1) channel bandwidth partitioning

Note that the figure illustrates the case where the scheduler actually has

traffic to fill the guaranteed portion of the channel. If that were not the

case then in theory the scheduler can temporarily borrow the guaranteed


4 - 23

bandwidth to satisfy non-guaranteed bandwidth requests. For capacity

estimations we need to assume the worst case where the guaranteed

bandwidth is in use.

This should not come as a surprise; the base station scheduler design

is similarly not described by the standard. The authors of the standard

were trying to balance the conflicting requirements of creating a standard

while allowing freedom where possible for product differentiation and

innovation.

One simple way to deal with the issue might be to implement a

policy of fair-sharing the non-guaranteed bandwidth between VBR and

BE. That is, equally divide any remaining bandwidth up between all

requesting VBR and BE service flows. The problem with this approach is

that is does not allow service providers much control to differentiate their

services. The other problem is that, while VBR can specify a minimum

information rate, BE services under severe congestion can be starved with

throughput rates approaching zero. A better solution is to provide a

method for prioritizing access to non-guaranteed bandwidth, which can

be done by introducing the concept of service flow over-subscription.

4.4.6 Quality of service (QoS) Control modeling

Dimensioning a network needs to keep in mind the user traffic

demand and the applications it uses so that the density of Base Stations

and backbone network dimensioning can fulfill the demand. Another

important task in service provision is to support the QoS parameters of

each connection over the demanded bandwidth. In our current algorithm

we benefit two Over Subscription Ratio (OSR) and Contention Ratio


4 - 24

(CR) measures in order to apply quality of service (QoS) control over the

expected traffic that will be explained in this section.

4.4.7 Contention Ratio (CR)

As the customer base is growing, there must be a measure of the

simultaneity of users requesting bit rate from the Base Stations because

most users won’t demand data at the same time. In simplest terms it

means that, the absolute peak demand on shared resources rarely occurs.

This user simultaneity is defined by a parameter we call contention ratio.

On the other hand, many of the connected subscribers will demand

data whose packets can be delivered assuming some latency or jitter i.e.

less priority.

The available channel bandwidth can be allocated to the users in a

guaranteed and non-guaranteed moods based on the applications.

Generally, applying a contention ratio (CR) for the guaranteed bandwidth

is a practice that operators should approach with caution since their

customers naturally expect that their service agreements will be honored

always. In our algorithm, no Contention Ratio is applied over the

guaranteed partition of the channel bandwidth. However, in future

developments assigning a CR over reserved bandwidths that correspond

to the error or blocking probability of each application will result in a

more accurate traffic modelling. According to the algorithm proceeded in

this thesis, two contention ratios are defined for the non-guaranteed

partition of the bandwidth. Typical values for contention ratios can be

about 30 for residential users (less priority) up to 10 for business users

(higher priority and throughput).In this case, if a Residential Class and a

Business Class Subscribers have contracted a downlink BE service of the


4 - 25

rates 512 kbps and 1Mbps respectively, 512/30=17 kbps and

1000/10=100 kbps are the actual data-rates that must be considered in the

system total capacity calculations. This is while the data rate of the

services with guaranteed bandwidth (CBR,VBRMR) will remain

untouched. Figure (2) illustrates the distribution of two different service

classes traffic model.

4.4.8 Over Subscription Ratio (OSR)

Over-subscription ratio, sometimes called over-booking ratio, in

simplest terms means taking advantage of the fact that, for many systems,

absolute peak demand on shared resources rarely occur. Examples are

everywhere in daily life. Air lines aggressively over-subscribe their seat

capacity. Public telephone networks over-subscribe their network

switching capacity. The point of over-subscription is that system capacity

requirements can be significantly reduced if the requirement to handle

absolute worst-case scenarios is ignored. However, over-subscription

comes at a price that is related to trading hard guarantees of service for

soft statistical guarantees. Depending on the nature of shared resource

usage i.e. the traffic, and how aggressively the resource is over-

subscribed, there can be exceptional periods where there is more demand

than can be served.

The standard also includes the ability to specify a traffic priority

QoS parameter for VBR and BE service flows. This allows basic

grouping of priority between sets of service flows. However, it does not

distinguish between guaranteed and non-guaranteed VBR traffic or allow

division of priority beyond eight basic levels.


4 - 26

How mathematically rigorous the statistics of the guarantees are

usually depends on how much is known about the offered traffic. One

well-known example is the blocking probability associated with

traditional voice Erlang statistics. On the other hand, mixed application

packet data networks are notoriously difficult to treat with statistical

methods for the general case. Often this results in resorting to empirical

rules derived from traffic measurements of a given user population.

In the case of mobile networks, operators can choose to over-

subscribe the total network capacity in order to improve overall network

utilization and cost per line business economics. There are two basic

scenarios. An operator can choose to over-subscribe one or more service

flow’s ‘guaranteed’ bandwidth, or they might choose to over-subscribe

their non-guaranteed bandwidth.

Generally over-subscription of guaranteed bandwidth is a practice

that operators approach with caution since their customers naturally

expect that their service agreements will be honored always. But the fine

print of these agreements may also allow for hopefully rare periods when

the network will not be able to support the guaranteed performance. One

simple example could be that voice over internet protocol (VoIP) users

are guaranteed that less than 1% of their call attempts will be blocked.

This can be accomplished by using Erlang statistics to reserve an over-

subscribed block of bandwidth sufficient to support a given number of

voice lines.

Over-subscription of non-guaranteed bandwidth is of course fair

game but an operator must still balance their users’ service level

expectations against the degree of over-subscription of the network


4 - 27

capacity. If users are told that they can expect “up to” some peak level of

service but discover that during busy hours that they can only get one

tenth of that service they will likely be dissatisfied with their service.

Often this is handled by marketing a “typical” level of service associated

with a given level of over-subscription (related to the total number of

users) and an “up to” service rate limit.

Returning to the issue of shared non-guaranteed bandwidth between

VBR and BE service flows, one solution for prioritizing the access would

be to associate a level of over-subscription to each service flow. For VBR

flows there are two relevant independent levels of over-subscription, one

for the guaranteed Minimum Reserved portion, and a second for the non-

guaranteed portion corresponding to rates bounded by the Minimum

Reserved and the Maximum Sustained limits.

For BE flows there is just one level of over-subscription associated

with the Maximum Sustained limit. If the system allows the service flows

to be configured in this manner then the relative priority ranking of the

non-guaranteed portions of the VBR and BE service flows can be

accomplished. This in turn allows operators to calculate the total number

of lines of service that can be provisioned for a given service scenario.

The problem of allocating the aggregate system capacity to the

various service flows must take into account the QoS requirements of

those flows. Dedicated or guaranteed bandwidth must be dealt with first

and what remains is shared by non-guaranteed services.

OSR is the ratio of the total subscriber’s demand over the reference

capacity of the base station when taking into account the adaptive


4 - 28

modulation. The reference capacity of the base station corresponds to the

available bit rate of the lowest modulation scheme served with that BS.

Subscriber classes distribution model

Consider the two subscriber classes i.e. business and residential.

Assume that the residential class occupies 58% of the users under cover

of our base station while the business class users are confined to 42%. As

shown in table (4.3).

Subscriber class Percentage or weight%

Business subscriber class (B) 58%

Residential subscriber class (R) 42%

Table (4.7) subscriber class distribution model

The total subscriber’s demand capacity refers to the repartition of the

subscribers based on their type of service. In this case the total capacity

for OSR calculation would be:

Ctot=N× (PR×BWR+ PR×BWB) Equation (4-20)

Ctot = N × (58% x 512 + 42% x 1000)

OSR = Ctot /Cref Equation (4-21)

Where

N refers to the number of users that are connected to the base

station (BS).

OSR is a measure of QoS in cell planning. A fair trade off

between OSR and CRs of traffic model will provide us with a

good measure of QoS control. This is because of the fact that the


4 - 29

CRs help us to have a realistic model of the in use traffic based on

the modulation distribution of the subscribers within the coverage

area, while the OSR gives us an idea about the traffic demand that

the operator has committed.

4.4.9 Application or service Distribution and Market Trends

Therefore, studying the traffic demand of existing service providers

can give us an idea about the subscribers’ possible application

distribution while using metropolitan broadband wireless services.

As can be seen, the most significant usage belongs to HTTP web

browsing applications. While the total percentage of the point to point

(p2p) services is almost 60% of all traffic, due to applying bandwidth

limitation over point to point (p2p) in October it drops to 14%. Streaming

traffic increased from 1.24% 12.5% mainly because of submission of

mobile TV.

These values are used to model our application distribution. Table

(4.3) summarizes this model which is the final distribution that will be

taken in to consideration in our capacity calculation algorithm.

Figure (4-2) subscriber class deployment model


4 - 30

4.4.10 Subscribers’ traffic demand

Now that all application distribution parameters are completely

defined, the minimum bandwidth of the demanding traffic can be

calculated. The phrase minimum demand here signifies that we are only

relying on the minimum reserved data-rate required for the applications

including guaranteed bandwidth.

Subscriber class

Business subscriber class (BWB) 1Mbps

Residential subscriber class (BWR) 512 Kbps

Table (4.8) subscriber class traffic model

This fact enables us to derive the maximum supportable capacity of

a generic sector. In our algorithm, the traffic demand is categorized into 2

subscriber classes. Adding more classes is an easy task and won’t change

The relations below conduct traffic demand calculation path for

residential and business class subscribers and the Total Traffic Demand

for DL.

DRresrved=P1×DR1+P2×DR2+P3×DR3 Equation (4-22)

DRreserved = 25% x 50 + 10% x 32 + 12.5% x 64

DRshared-R=P4×DR4+P5 × (BWR-(DR1+DR2+DR3) Equation (4-23)

DRshared-R = 32.5% x BWR + 20% x (BWR - (50+32+64)

DRshared-B=P4×DR4+P5 × (BWB-(DR1+DR2+DR3) Equation (4-24)

DRshared-B = 32.5% x BWB + 20% x (BWB - (50+32+64))

Traffic R = N x (%PR) x (DRreserved + (DRshared-R / CR R) Equation (4-25)


4 - 31

Traffic B = N x (%PB) x (DRreserved + (DRshared-B / CR B) Equation (4-26)

Traffic Total = Traffic R + Traffic B

The parameters are as follow:

DRreserved: Minimum Reserved (Guaranteed) Data-rate for CBR/VBR

Applications

DRshared-R : Shared Data-rate for Residential Class users with BE

Applications

DRshared-B: Shared Data-rate for Business Class users with BE

Applications

BWR: Residential class subscribers data-rate based on user agreement

BWB : Business class Subscribers data-rate based on user agreement

N: Total number of the users connected to the sector

%PR: Percentage of the residential class subscribers within the area

under study

CR R: Contention Ratio for residential class subscribers

%PB: Percentage of the business class subscribers within the area under

study

CRB: Contention Ratio for business class subscribers

Chapter FiveNumerical Results

Chapter 5: Numerical Results

5 - 2

Chapter FiveNumerical Results

Flow chart of Project Work

Start

Preliminary study about LTE

Problem specific study andReview of the related works

Theoretical Understanding(Input/output specification, etc)

Basic Dimensioning Tool started

Work on LTE Dimensioningand Tool

Coverage Planning (Radio Link Budget,Number of sites needed

based on Capacity)Capacity Evaluation

Review: Is thework complete?

Proceed with documentation

End


5 - 3

5.1 Up Link Budget

5.1.1 User Equipment effective Isotropic Radiated Power (EIRP):-

Figure (5-1) flowchart of effective isotropic radiated power

Figure (5-2) Calculation of EIRP

EIRP

Transmittedpower per PRB

Gain

-H/B losses


5 - 4

Inputs:-n’PRbsUE antenna GainP(UE)P(UE,PRB)Other GainsHead Body lossOutput:-EIRP(UE)Equation:-P(UE,PRB) =EIRPUE,PRB = PUE,PRB + GUE + Gothers – LHBLWhere:-n’PRBs: Number of Physical Resource BlocksPUE: user equipment output PowerP(UE,PRB): Power per Physical Resource BlocksGUE: User equipment transmitting antenna gain [dBi]LHBL : head body loss [dB]G others : It is gains due to MIMOEIRPUE,PRB: Effective Isotropic Radiated Power.

Excel Results

Coverage (UL)---- RL budget1-UE parameters

Item Unit ValuesP(UE) dBm 23P(UE) Watt 199.5262315

Channel B.W MHz 20nPRB PRBs 100

P(UE.PRB) Watt 1.995262315P(UE,PRB) dBm 33

UE Tx gain dBi 0other UE gain dBi 2L(HBL) in VOIP dB 3EIRP (UE,PRB) dBm 32

Table (5-1) EIRP


5 - 5

5.1.2 Enhanced NodeB Sensitivity:

-

Figure (5-3) flowchart of sensitivity of eNodeB

Figure (5-4) Sensitivity of Enhanced nodeB

Sensitivity

Thermal noise

Noise figure

Log Wprb(B.Wper PRB)

SINR


5 - 6

Inputs:-KTNtNflogWPRBa0a1a2a3γtarget

Output:-SeNodeBSINRN(PRB,UL)Equation:-SeNodeB= Nt + Nf + logWPRB +γtarget,UL

Where:- Nt: It is thermal noise power density Nf: noise figure of receiver Wprb : bandwidth per physical resourse block γtarget,UL: SINR requirement for uplink traffic channel

Excel Results2-BS parameter

Item Unit ValuesBoltzman constant J/K 1.38E-23

Ambient temperature K 290Thermal noise power density (Nt) dBm/Hz -174

Noise figure of eNodeB (Nf) dB 2BW per resource block [W(PRB)] MHz 0.18

a0 Kbps 536.6a1 dB 20.76a2 dB 13.28a3 Kbps 0

Bit rate [R(PRB)] Kbps 64SINR dB -2.499734217

Sensitivity of e.NoodeB dB -181.9470092

Table (5-2) Default values of Enhanced eNodeB sensitivity


5 - 7

5.1.3 Interference Margin (IM)

Figure (5-5) flowchart of Interference Margin

5.1.4 Log Normal Fading Margin (BLNF)

Figure (5-6) flowchart of Log Normal Fading Margin


5 - 7






5 - 7






5 - 8

5.1.5 Total Margins:-

Figure (5-7) flowchart of total margins

Figure (5-8) Total margin

Inputs:-SINR (Gamma)Q'8UL


5 - 8






5 - 8






5 - 9

Interference Factor (F)µσP%LNFBI (UL)FFMOutputs:-(IM) BIULBLNFTotal MarginsEquation:-

BIUL= , , ,BLM= norm inverse (P%,µ,σ)Total Margins= LNF+ BI(UL)+ FFMWhere:-γ target,Ul: Is the SINR target for the Uplink open loop Power ControlQUE: Is the average Uplink System loadF : It is the average ratio of Path gains for interfering cells to those of theserving cell.µ: is the mean of lognormalσ : is the standard deviation of lognormalP : is the coverage probabilityLNF: log normal fading marginsBI(UL): Interference marginFFM: fast fading margin

5-MarginsItem Unit Values

Mean of Log normal (µ) --------- 0Standard Deviation (σ) dB 3

Area of Coverage Flat Areaedge Coverage Prob. F(p) % 90

Lognormal Fading Margin [B(LNF)] dB 3.844654697Cell Loading Factor [Q(UL)] --------- 0.64

F --------- 0.7B(IUL) dB 1.26066082

Fast Fading Margin [B(FFM)] dB 2Total Margin dB

Table (5-3) Default values Total margin


5 - 10

5.1.6 Total Gains:-

Figure (5-9) flowchart of total gains5.1.7 Total Losses

Figure (5-10) flowchart of total losses

Connectorloss

Connectorspecifications

Connectorlength

Jumperloss

Jumperspecifications

Jumperlength

Carpenetration

loss

Head/body loss Buildingpenetration loss

Total losses


5 - 10

5.1.6 Total Gains:-



Connectorloss


Connectorlength

Jumperloss


Jumperlength

Carpenetration

loss


Total losses


5 - 10

5.1.6 Total Gains:-



Connectorloss


Connectorlength

Jumperloss


Jumperlength

Carpenetration

loss


Total losses


5 - 11

Figure (5-11) total gains and total lossesInputs:-G1G2BPLCPLJumper LengthJumper LossFeeder lengthFeeder lossContactor lossoutputs:-Gt: Total GainsTotal LossesEquation:-Total Gains = eNodeB antenna Gain + Other GainsTotal Losses= BPL+ CPL+ Jumper Length+ Jumper Loss+ Feederlength+ Feeder loss+ Contactor lossWhere:-G1: eNodeB antenna Gain


5 - 12

G2: Other gainsGt : Total GainsBPL: Building Penetration LossCPL: Car penetration loss

4-other eNodeB parameterItem Unit Values

Gain of e.NodeB dBi 18Other gain of e.NodeB dBi 4

Total Gain dBi 22Building Pentration Loss [LBPL] dBi 15

Car Penteration Loss [LCPL] dBi 9BS Feeder Specification (dB/100m) 3e.NodeB Feeder Length Meter 30

e.NodeB Feeder Loss (Lf) dB 1.05e.NodeB Jumper Specification dB/100m 2

e.NodeB Jumper Length Meter 5e.NodeB Jumper Loss (Lj) dB 0.1

e.NodeB Connector Loss (Lc) dB 1Total Loss dB 26.15

Table (5-4) Total Losses and Gain

5.1.8 Maximum Allowable Paths Loss (MAPL)

Figure (5-12) flowchart of maximum allowable path loss

MAPL

EIRP

Gain

-Losses

-margins

-Sensitivity ofeNodeB


5 - 13

Figure (5-13) Max. Allowable path loss in using GUI in Matlab

Inputs:-EIRP(UE,PRB)SeNodeBTotal losses (LBPL + LCPL + LeNodeB +Lj +LC )Total Gains (GeNodeB + Gother)Total margins (BLNF + BIul)Output:-MAPLUL

Equation:-MAPLUL=EIRPUL,PRB – SeNodeB – (BLNF + BIul) – (LBPL + LCPL + LeNodeB +Lj +LC ) + (GeNodeB + Gother)

Where:-BLNF: lognormal fading margin [dB]BIul: UL interference Margin [dB]LCPL: car penetration loss [dB]LBPL: Building Penetration LossGeNodeB: eNodeB Reciever antenna gainGother: is other Gain [dBi]


5 - 14

Lf eNodeB: is eNodeB feeder loss [dB]Lj: jumper lossLC: connector loss

Excel Results

6-Max allowable path lossItem Unit Values

MAPL dB 202.6916936

Table (5-5) Default values of Maximum allowable path loss (MAPL)

5.1.9 Cell Radius Using Ericson Variant Okumura-Hata

Figure (5-14) flowchart of cell radius using Ericson variant Okumara -Hata


5 - 14


Excel Results


MAPL dB 202.6916936





5 - 14


Excel Results


MAPL dB 202.6916936





5 - 15

5.1.10 Site Count

Figure (5-15) flowchart of site count

Figure (5-16) cell radius and Site Count

Inputs:-MAPLhb


5 - 15

5.1.10 Site Count



Inputs:-MAPLhb


5 - 15

5.1.10 Site Count



Inputs:-MAPLhb


5 - 16

hma(hm)FrequencyADeployment AreaCell RadiusCell AreaOutputs:-R in kilometersSite CountEquation:-R=10α

α=

Site Count =

Where:-Lo= A+13.82loghb+ a(hm)ϒ= 44.9 – 6.55loghbMAPL: maximum allowable paths losshb: base station or eNodeB antenna height [m]hm: height of user equipment antenna [m]a(hm): inverse relationshipis written as followsMAPL=A – 13.8loghb – a(hm) + (44.9 – 6.55log hb)log RA: frequency-dependent fixed attenuation valueSc: site count =

Table (5-6) values of Cell Radius and Site count with difference Basestations heights


5 - 17

5.2 Effects on cell Radius (R)In the following subsections the effect of the following parameters will beinvestigated

1- Effect of cell types, we will considered omni cell and 3 sectors cell2- Impact of different morphologies, we will considered Rural.

Suburban and Urban.3- Effect of cell loading factor4- Effect of eNodeB antenna height

5.2.1 The effect of cell Loading Factor (Q) on the cell Radius (R)Omni

Table (5-7) the effect of cell Loading Factor (Q) on the cell Radius (R)Omni

Figure (5-17) the effect of cell Loading Factor (Q) on the cell Radius (R)Omni

CLF 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9RUcell R

599.4749

592.2286

584.7593

577.0495

569.0798

560.828

552.2687

543.3728

534.1065

UR 66.50882

65.7482

64.96365

64.15327

63.31495

62.44628

61.54451

60.60648

59.62851

SU 162.179

160.2639

158.2893

156.2505

154.1423

151.9588

149.6931

147.3374

144.8827

DU 218.58 216.135

213.6123

211.0059

208.3088

205.5133

202.6104

199.5898

196.4394


5 - 18

We conclude that in case of omni cell as cell loading factor increase cellradius decreases for different types of morphologiesFor certain cell loading factor the cell radius increase as we go fromurban to suburban to ruralFor example for cell loading factor 50%Cell radius in urban = 63.31495 KmCell radius in suburban = 154.1423 KmCell radius for rural = 569.0798 Km

5.2.2 The effect of cell Loading Factor (Q) on the cell Radius (R) 3Sector

Table (5-8) the effect of cell Loading Factor (Q) on the cell Radius (R) 3sector

Figure (5-18) the effect of cell Loading Factor (Q) on the cell Radius (R)3 sector

h(B)/meter 10 20 30 40 50 60 70 80 90 100

RU cellR

253.1066

444.5555

636.3798

832.8866

1035.47

1244.719

1460.917

1684.21

1914.677

2152.359

UR 56.07967

90.7723

123.3535

155.2647

187.0305

218.9044

251.028

283.4883

316.3421

349.6283

SU 96.84865

161.4741

223.6102

285.4681

347.8312

411.0675

475.3765

540.8769

607.6433

675.7252

DU 215.7335

375.6464

534.7792

697.0233

863.6646

1035.261

1212.091

1394.3

1581.973

1775.158


5 - 19

We conclude that for 3 sector cell the same result as omni cell but moreover cell radius of 3 sector cell is larger than cell radius of omni cell onall morphologies For example for cell loading factor 50%Cell radius in urban = 92.56354 KmCell radius in suburban = 228.1687 KmCell radius for rural = 850.2738 Km

5.2.3 Effect of eNodeB antenna height on Cell Radius in omni cell

h(B)/meter 10 20 30 40 50 60 70 80 90 100

RU cellR

176.5427

304.0831

429.9145

557.4427

687.8188

821.5555

958.9149

1100.043

1245.025

1393.912

UR 39.11576

62.08971

83.33301

103.9171

124.2365

144.4842

164.7695

185.1606

205.7025

226.4265

SU 67.55226

110.4509

151.0628

191.0609

231.0496

271.3182

312.0271

353.274

395.1219

437.6136

DU 150.4748

256.9482

361.2769

466.5107

573.696

683.3069

795.5906

910.6878

1028.683

1149.629

Table (5-9) the effect of eNodeB antenna height on the cell Radius (R)omni

Figure (5-19) the effect of eNodeB antenna height on the cell

Radius (R) omin


5 - 20

We conclude that the cell radius of Omni cell increases as eNodeB antenna

height increase for different types of morphologies for certain eNodeB antenna

height for example h = 30 m

Cell radius in urban = 83.33301 Km

Cell radius in suburban =151.0628 Km

Cell radius in rural = 83.33301 Km

5.2.4 Effect of eNodeB antenna height types on Cell Radius in 3-

sector cell

h(B)/meter 10 20 30 40 50 60 70 80 90 100

RU cellR

253.1066

444.5555

636.3798

832.8866

1035.47

1244.719

1460.917

1684.21

1914.677

2152.359

UR 56.07967

90.7723

123.3535

155.2647

187.0305

218.9044

251.028

283.4883

316.3421

349.6283

SU 96.84865

161.4741

223.6102

285.4681

347.8312

411.0675

475.3765

540.8769

607.6433

675.7252

DU 215.7335

375.6464

534.7792

697.0233

863.6646

1035.261

1212.091

1394.3

1581.973

1775.158

Table (5-10) the effect of eNodeB antenna height on the cell Radius (R) 3sector

Figure (5-20) the effect of eNodeB antenna height on the cell Radius (R)

3 sector


5 - 21

For 3 sector cell the same results as omni cell but more over cell radius of

3 sector cell is larger than cell radius of omni cell

For 3 sector cell for certain eNodeB antenna height for example h = 30 m

Cell radius in urban = 123.3535 Km

Cell radius in suburban = 223.6102 Km

Cell radius in rural = 636.3798 Km

5.3 Downlink capacity

Figure (5-21) downlink capacityInputs:-MAPLLNF marginTotal GainTotal LossesP (norm,ref)N (PRB)Q (CLF)HChannel ModelOver Booking Factor


5 - 22

Subscriber ClassSubscriber Data rateCode rateNumber of userApplication services

Outputs:-L (sa,max,DL)P (e Node B,PRB)R(PRB,DL)Interface Margine (BIDL)SINRRavg,DLTotal Through putNumber of cell required (Nrequired)

T cell,DL

Equation:-

Nrequired = Tt/Tsite


5 - 23

RAVG,DL = RRB,DL (nRB,DL - nPDCCH)

Tsite = Tcell,DL × number of active users (U)

Tsite = Tcell,DL (Omni cell )

Tsite = 3 × Tcell (3 sector cell)

Ttotal = U × TU × (OBF)

Nsite =

Ctot=N× (PR×BWR+ PR×BWB)

C tot = N × (58% x 512 + 42% x 1000)

OBF = Ctot /Cref

DRresrved=P1×DR1+P2×DR2+P3×DR3

DRreserved = 25% x 50 + 10% x 32 + 12.5% x 64

DRshared-R=P4×DR4+P5 × (BWR-(DR1+DR2+DR3)

DRshared-R = 32.5% x BWR + 20% x (BWR - (50+32+64)

DRshared-B=P4×DR4+P5 × (BWB-(DR1+DR2+DR3)

DRshared-B = 32.5% x BWB + 20% x (BWB - (50+32+64))

Traffic R = N x (%PR) x (DRreserved + (DRshared-R / CR R)

Traffic B = N x (%PB) x (DRreserved + (DRshared-B / CR B)

Traffic Total = Traffic R + Traffic B = Tu × OBF

• Where:-

n'PRBs : number of physical resourse block


5 - 24

• RPRB,DL : Down Link data rate per physical resourse block

• (nPUCCH) : number of physical DL control channels

• QDL : The average downlink system load

• T(user) : Throughput for user

• B(IDL) : Downlink Interference margin (IM) or noise rise

• P(eNodeB,DL) : eNodeB transmitted or radiated power per physical

resourse block

• N(PRB,DL) : Down Link thermal noise per physical resourse block

• L(sa,max) : Maximum Down Link signal attenuation

• H : The average attenuation

• R(avrege,DL) : Average Downl Link data rate

• T(cell,DL) : The Downl Link data rate

• T(total) : Total Throughput

• T(site) : Throughput for site

• SINR(DL,avg) : Average Downl Link signal to interference and

noise ratio

• DRreserved: Minimum Reserved (Guaranteed) Data-rate for

CBR/VBR Applications

• DRshared-R : Shared Data-rate for Residential Class users with BE

Applications


5 - 25

• DRshared-B: Shared Data-rate for Business Class users with BE

Applications

• BWR: Residential class subscribers data-rate based on user

agreement

• BWB : Business class Subscribers data-rate based on user

agreement

• N: Total number of the users connected to the sector

• %PR: Percentage of the residential class subscribers within the area

under study

• CR R: Contention Ratio for residential class subscribers

• %PB: Percentage of the business class subscribers within the area

under study

• CR B: Contention Ratio for business class subscribers

Chapter SixConclusion and Suggestions for future work

Chapter 6: Conclusion and Suggestions for future work

6 - 2

Chapter sixConclusion and Suggestions for future work

6.1 Conclusions

In this project, we study LTE network coverage and capacitydimensioning.Dimensioning process is a part of planning process and provides thenetwork elements count as well as the capacity of those elements.We considered only access network dimensioning .Thus; the output of thedimensioning is the number of eNodeB that fulfil coverage and capacityrequirements.LTE coverage dimensioning is done via radio link budget (RLB) andsuitable propagation models .The output of RLB is the MAPL.Then using a suitable propagation model, the cell radius is obtained.Cell radius is used to obtain site count.LTE capacity dimensioning is obtained, given the number of subscribers,their demanded services and subscriber usage level. The cell radius basedon capacity is determined.Two values of cell radius are obtained:▪ One from coverage dimensioning▪ Second from capacity dimensioning the larger of the two numbers istaken as the final output

We get in consider the effect of the following parameters

1- Effect of cell types, we will considered omni cell and 3 sectors cell2- Impact of different morphologies, we will considered Rural.

Suburban and Urban.3- Effect of cell loading factor4- Effect of eNodeB antenna height

The effect of cell Loading Factor (Q) on the cell Radius (R) Omni cell

We conclude that in case of Omni cell as cell loading factor increase cell radiusdecreases for different types of morphologiesFor certain cell loading factor the cell radius increase as we go from urban tosuburban to ruralFor example for cell loading factor 50% cell radiuscell radius in urban = 63.31495 KmCell radius in suburban = 154.1423 KmCell radius for rural = 569.0798 Km


6 - 3

The effect of cell Loading Factor (Q) on the cell Radius (R) 3 Sector

We conclude that for 3 sector cell the same result as omni cell but moreover cell radius of 3 sector cell is larger than cell radius of omni cell onall morphologiesFor example for cell loading factor 50%Cell radius in urban = 92.56354 KmCell radius in suburban = 228.1687 KmCell radius for rural = 850.2738 Km

Effect of eNodeB antenna height on Cell Radius in omni cell

We conclude that the cell radius of omni cell increases as eNodeBantenna height increase for different types of morphologiesFor certain eNodeB antenna height cell radius increases as we go fromurban to suburban to rural for certain eNodeB antenna height for exampleh = 30 mCell radius in urban = 83.33301 KmCell radius in suburban =151.0628 KmCell radius in rural = 83.33301 Km

Effect of eNodeB antenna height on Cell Radius in 3 sector cell

For 3 sector cell the same results as omni cell but more over cell radius of3 sector cell is larger than cell radius of omni cellFor 3 sector cell For certain eNodeB antenna height for example h = 30 mCell radius in urban = 123.3535 KmCell radius in suburban = 223.6102 KmCell radius in rural = 636.3798 KmFinally, a dimension tool is developed.In this project, interference system based capacity dimensioning isstudied.


6 - 4

6.2 Suggestions for future work

In this project we considered only LTE coverage and capacitydimensioning. Data analysis, Traffic analysis and Transportdimensioning can be studied in the future.

In this project, we considered only access network, LTE corenetwork can be studied to determine core network nodes and thenumber of backhaul links required.

In this project, we considered VOIP only, other services such asweb browsing, file transfer and multimedia can be studiedindividually, then developing traffic model for user includingmixed services.

Detail LTE planning that include in addition to coverage andcapacity dimensioning: frequency planning, neighbour planningand parameter planning, finally a planning tools is developed.

In addition to introducing digital three dimensional (3D) mapwhich is imported in the planning tool as real prediction andsimulations of the RF signal level in a real traffic distribution.

Other methods for capacity dimensioning such as cell ring basedcapacity method and modulation based capacity dimensioningmethod can be studied.

In this project, we consider FDD (Frequency Division Duplex), inthe future we can use TDD (Time Division Duplex) or half duplex.

References

1) 3GPP Technical Report TR 25.813, “Radio Interface Protocol Aspects for

Evolved UTRA”, version 7.0.0

2) “Long Term Evolution (LTE): an introduction,” Ericsson White paper,

October 2007.

3) Dahlman, Parkvall, Skold and Beming, 3G Evolution: HSPA and LTE for

Mobile Broadband, Academic Press, Oxford, UK, 2007.

4) Indoor radio planning : A practical guide for GSM, UMTS, HSPA, LTE ,

Second edition ,MortenTolstup, 2011 John Willey sons.

5) Wiley-VCH Verlag GmbH, Boschstrasse 12, D-69469 Weinheim, Germany

6) Jossey-Bass, 989 Market Street, San Francisco, CA 94103-1741, USA

7) Abdul Basit Syed, Description of Models and Tool, Coverage and Capacity

Estimation of 3GPP Long Term Evolution, February, 2009

.