Effect Adjacent Terhadap Kapasitas Uplink

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326 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 52, NO. 2, MARCH 2003

Effect of Adjacent IS-95 Network to WCDMAUplink Capacity

Kari Heiska

AbstractThis paper derives the degradation of the wide-bandcode-division multiple-access (WCDMA) uplink capacity in thesituation where the IS-95 system is deployed at the adjacentfrequency band. A system modeling approach that combines anaccurate pathloss information with simplified and computation-ally fast interference modeling is described here as well. Themodel takes into account the power-control coupling betweenIS-95 and WCDMA systems as well as the effect of downlinkblocking. This paper includes also some numerical examplesfrom realistic micro- and macrocellular network scenarios. Theresults show that the interference is dependent, in addition to thefilter characteristics, on the used network scenario, whether theinterfered or interfering system is microcellular or macrocellular,and on the relative cell densities of the interfering and interferednetworks. The developed method can be utilized for WCDMAnetwork planning, for frequency allocation, and for system designof the mobile telecommunication systems.

Index TermsAdjacent system interference, capacity, IS-95,mobile communications, wide-band code-division multiple-access(WCDMA).

I. INTRODUCTION

WIDEBAND code-division multiple access (WCDMA)

is the most applicable candidate for providing Uni-

versal Mobile Telecommunications System (UMTS) services

worldwide in the future. It enables a large variety of dif-

ferent mobile multimedia services with wide areal coverage.The planning and parameterization of the third-generation

(3G) radio network is, however, more challenging than the

second-generation system because of its multidimensionality.

In the 3G systems, the planner has to be able to guarantee a

certain quality-of-service (QoS) level for various service types

and bit rates. Additionally, the performance optimization of

the WCDMA system becomes essential in order to increase

the profitability of the network. This is emphasized especially

when utilizing the WCDMA system spectrally adjacent to other

mobile technologies.

The WCDMA system is typically interference limited. This

means that the capacity and the coverage is normally limited

only by the interference coming from the geographically

or spectrally adjacent base stations and mobile stations in

downlink and uplink directions, respectively. This interference

can be originated from the carriers of the own or the adjacent

operator. In the UMTS frequency-division duplexing core

band (19201980 MHz in uplink and 21102170 MHz in

downlink), this adjacent operator interference originates from

Manuscript received May 17, 2001; revised June 19, 2002.The author is with Nokia Corporation, Espoo 02600, Finland.Digital Object Identifier 10.1109/TVT.2003.808748

the WCDMA system itself. The interference between two

WCDMA operators has been investigated, for example, in [1]

and [2]. However, in the case when the WCDMA frequencies

will be reframed to an existing frequency bandfor example,

to PCS bandthis interference may originate from some other

system as well [3], [4]. The adjacent operator interference is

usually quite significant because the cells of two operators are

geographically independently located.

In this paper, we are concentrating on the uplink capacity re-

duction of the WCDMA system when the WCDMA and IS-95

system are spectrally adjacent to each other and operated by dif-

ferent operators, assuming that the sites of two networks are in-dependently located. The assumed frequency allocation and the

basic interference coupling scenario has been depicted in Fig. 1.

II. UPLINK INTERFERENCE MODEL

The out-of-band interference from the IS-95 terminals

increases the interference levels at the spectrally adjacent

WCDMA base-station receiver, which also increases the

needed power at the mobile terminals through the uplink (UL)

power control of the WCDMA system. This, in turn, affects

the interference at the IS-95 base stations, which subsequently

increases the IS-95 terminal powers through the IS-95 power

control, and so on. The strength of the coupling between these

two systems is dependent on the filtering characteristics at base

station (BS) and mobile station (MS) at the transmission and at

the reception, as well as on the locations of the cells.

The increased uplink interference requires more transmission

power at the mobile terminals, which in turn decreases the cov-

erage of the cell. The number of own-cell users increases the

interference, which is usually referred to as the noise rise of the

system. To provide constant quality for a given service, which

here means satisfactory coverage, the coverage threshold has to

be stable enough. The uplink capacity has been defined here as

the maximum number of users in the own cell for which the total

interference level at the BS is lower than the target value. The

total average interference in one cell in the WCDMA systemcan be written by

(1)

and in the IS-95 system by

(2)

where and depict the interference caused by the

own-cell users, and are the interference from the

adjacent cells of the own system, and and are

0018-9545/03$17.00 2003 IEEE
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HEISKA: EFFECT OF ADJACENT IS-95 NETWORK TO WCDMA UPLINK CAPACITY 327

Fig. 1. Interference coupling between two CDMA systems operated at adjacent frequency bands.

the interference from the IS-95 system to WCDMA and vice

versa. Here, we have assumed that there are an equal number of

users in each cell having the similar service distribution. These

equations can be written more specifically by

(3)

and

(4)

where and are the average interference levels of the

WCDMA and IS-95 base stations. refers to pathloss

from the cell , which is either IS-95 cell ( ) or WCDMAcell ( ), to mobile connected to cell . The bit rates of the

mobile in the WCDMA system mobile and the mobile in

the IS-95 system are and , respectively. and are

the chip rates of the WCDMA system and IS-95 systems. The

values giving the required frame error rate (FER)/bit

error rate target are and , and the respective soft-handover

gains are and for the WCDMA mobile and

IS-95 mobile. and are the thermal noise powers for

the systems, including also the noise figure of the base-station

receiver. The number of users per cell in the WCDMA system

and in the IS-95 system is and and the number of

cells in the WCDMA system and in the IS-95 system is

and , respectively. The soft handover overhead is assumed

to be and for WCDMA and IS-95 systems,

respectively, and defined as the total number of links per cell

divided by the number of best server users of the cell. The

modeling of SHO has been described more specifically in [5].

The power control increases the interference power to other

cells, which can be taken into account with an additional power

rise term in (3) and (4), as shown in [6]. However, this effect

has not been taken into account here.

The adjacent channel interference ratio from the WCDMA

system to IS-95 and from the IS-95 system to the WCDMAsystem is and , respectively. These can be computed

by convoluting the emission spectrum of the mobile and the re-

ceive filter of the base station. The power rise due to fast power

control has not been taken into account in these equations. When

each user is using the same bit rate ( and ),

we can then write as

(5)

where

(6)

and

(7)
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Fig. 2. Effect of downlink blocking.

where and

. The following notations have been used

for the pathloss ratios:

(8)

From (5), we can analyze the effect of the power-control cou-

pling between different systems and its effect to the uplink per-

formance. The model assumes infinite dynamic range of the MS

power control so that the maximum allowed transmission power

of the mobile terminal has not been taken into account.

To compute the interference levels ( and ), the distri-

bution of the pathloss ratios has to be known. Pathloss data for

each base station for the whole study area has been computed byusing appropriate propagation models. The propagation models

and network structures for the numerical examples have been

shown in Section III. Pathloss ratio distribution for one inter-

fering cell area has been computed from the pathloss maps of

interfering and interfered cells. The distribution includes those

pixels of the map to which the interfering base station has the

lowest pathloss. The sum distribution from interfering cells

can be defined with the iterative equation

(9)

where ) is the distribution of the pathloss ratio inside the

interfering cell and isthe distribution ofpathloss ratios

from cells. Thus, function ) gives the total pathloss

ratio distribution in the case of one interfering user in each cell.

In this paper, we have used average distribution over

all the cells in the system.

The possible downlink blocking has to be taken into account

when calculating the uplink interference. In the case of two

overlaid radio networks, the pathloss ratio between systems can

be significantly high in some cases. Consider, for example, the

case with WCDMA microcells and IS-95 macrocells. When an

IS-95 phone that is connected to its own, distant base station is

close to the WCDMA base station, the pathloss ratio and there-

fore the interference can be very high. However, in that case

also the WCDMA base station interferes with the IS-95 phone

in downlink and might block it before it will cause high interfer-

ence in uplink. This phenomena has been illustrated in Fig. 2.If we assume, for simplicity, that the only interference to the

IS-95 mobileis comingfrom the WCDMA base station operated

at the adjacent channel, we can write the signal-to-interference

ratio for the IS-95 mobile as

(10)

where is the requirement in the downlink, is

the maximum allowed transmit power from the IS-95 base sta-

tion, and is the transmit power of the WCDMA base sta-

tion. From this equation, the maximum allowed pathloss ratio

( ) between two systems can be defined

as

(11)

If the pathloss ratio is larger than , the mobile will be

blocked in downlink, in which case it will not cause any inter-

ference in uplink. The downlink power of the WCDMA system

varies as the load of the system changes, but in practice we

can use a value of 35 dB below the maximum power. The

maximum dedicated channel power in the IS-95 downlink

could be, for example, 10 dB below the maximum base station

power.

A. Propagation Models

The OkumuraHata propagation model (originally published

in [8] and [9]) was used when computing the pathloss maps for

themacrocell base stations. A ray-tracing model described in [7]

was utilized when computing the pathlosses in the microcellular

scenario. In the microcellular environment, the transmitting an-

tenna is below the rooftops, and the radiowave is propagating

through the street canyons. Therefore, the exact building coor-

dinates have to be known in order to predict the pathloss accu-

rately. The indoor penetration loss was computed according to

methods described in [10]. In the used scenario, the microcell

antennas were located at the street level with an antenna height
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of 10 m. The height of all the buildings was set to 25 m. The

cable attenuation between the BS and the antenna was assumed

to be 0 dB.

B. Network Scenarios

Five different urban cellular scenarios have been tested here.

1) Eight WCDMA macro base stations andfour IS-95 macrobase stations.

2) Eight WCDMA macro base stations and 12 IS-95 macro

base stations.

3) Eight WCDMA micro base stations and 16 IS-95 macro

base stations.

4) Twenty-oneWCDMA micro base stations andeightIS-95

macro base stations.

5) Twenty-one WCDMA micro base stations and 16 IS-95

macro base stations.

The worst case scenario from the WCDMA point of view is

the one having microcells utilized in the WCDMA system and

macrocells in the IS-95 system. This is because the interfering

IS-95 mobiles, connected to the macro base station, are usuallytransmitting with high powers and can therefore produce signif-

icantly high interference levels at the WCDMA receiver. Fur-

thermore, the minimum coupling losses are much lower in mi-

crocells than in macrocells. In microcells, they are on the order

of 5565 dB, but in macrocells, the minimum coupling losses

are well above 70 dB.

The pathloss differences within the system were well below

one, whereas the pathloss difference between the systems can

be very high60 dB, or even higher. Very high pathloss dif-

ferences are exceptional when both systems are macrocellular

[Cases 1) and 2)] compared to the case where the WCDMA

system is a microcellular system [Cases 3)5)]. This is because

the minimum coupling loss in a microcell can be very low (60 dB ) in some cases, giving usually a high value for .

When the WCDMA cells are microcells, the pathloss is

considerably low compared to , indicating that the pathloss

to the own WCDMA cell is relatively low compared to the

pathloss to the IS-95 cell. When comparing Cases 4) and 5),

we can see that in Case 4), is over 60 dB in some cases,

whereas in Case 5), it is usually well below 55 dB. This is

because in Case 4), the IS-95 network is less dense and the

pathlosses are typically higher than in Case 5). The pathloss

ratio within the own system indicates that in the case of micro-

cells, the isolation is much better than in dense macrocells.

C. Capacity Calculation Method

In CDMA systems, the additional interference in uplink de-

creases the maximum cell range. In the network planning, the

target is to guarantee the quality of the network, so that in the

cell area, the minimum required bit rate is fulfilled with a cer-

tain probability. Therefore, we have to set the target interference

level at the uplink that cannot be exceeded without decreasing

the quality of the network. The interference levels at the base

station in the case of overlapping radio networks can be com-

puted according to (5). This equation gives the interference sit-

uation with one mobile station distribution, assuming and

users in every WCDMA and IS-95 cell, respectively. This is

a highly varying variable, since when the locations of the mo-

biles change, also the pathloss difference changes, affecting the

interference levels. To compute the statistics of the interference

level, we have to generate several snapshots from the pathloss

difference distributions, compute the interference, and analyze

the distribution of the resulting interference. The capacity in up-

link can then be defined as the maximum number of users that

the system can serve without exceeding the target uplink inter-ference level more than percentage of cases. To compute the

capacity losses in uplink, we have to consider the distribution of

the uplink interference, with a fixed number of mobile station

users and over many mobile locations. That distribu-

tion can be produced by first generating and snapshots

of the pathloss difference by using the distributions shown in

(8) and summing the resulting random variable over the number

of users in order to produce a new random variable , ,

, or . These variablescan then beinserted into (5) in

order to compute the interference level , which is now a new

random variable. The capacity of the WCDMA system

can then be defined by using the probability

(12)

According to this assumption, the maximum capacity has been

reached when percentage of simulated samples are over the

target level . It has to be noted that the capacity of the

WCDMA system depends on the number of users in IS-95 sys-

tems and vice versa. The capacity reduction in the WCDMA is

then simply defined as by what percentage the capacity, with a

certain number of IS-95, of users is reduced compared to the

capacity of the noninterfered system. Here, we have assumed

that parameters , , , and are independent

from each other. This is, however, a valid assumption since the

mobiles are assumed to be located randomly inside the cell andcells in different systems are independently located.

Figs. 3 and 4 show the uplink interference level of each snap-

shot as a function of the number of users and with a constant

number of IS-95 users per cell (five users in Fig. 3 and 15 users

in Fig. 4). In these cases, there are 2000 snapshots generated

for every calculation point with constant and . It can be

seen that in some cases, the interference level increases rapidly

because of large interference peaks from the IS-95 mobiles.

III. RESULTS

The capacity reduction due to adjacent IS-95 system at a cer-

tain channel separation is dependent on the adjacent channelinterference, which is determined by the filter characteristics

in the transmission and reception, as well as on the particular

network and traffic scenarios of both systems. The density of

the networks and the typical locationing of the antennas (micro,

macro) have an impact to the capacity. The increased traffic in-

creases the probability of having high interference peaks. The

uplink capacity is dependent not only on the uplink but also on

the downlink filter characteristics. This is because the downlink

interference may block some mobiles, which might cause ad-

ditional interference in uplink, as explained in Section II. The

model presented in this paper assumes that the downlink ad-

jacent channel interference is the only interference source in


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Fig. 3. Uplink noise rise in a WCDMA microcell as a function of load inCase 4) (with five IS-95 users). The capacity of the noninterfered system is 50users and of the interfered system is 45 users. The channel separation here was3.225 MHz.

Fig. 4. Uplink noise rise a WCDMA microcell as a function of load inCase 4) (with 15 IS-95 users). The capacity of the noninterfered system is50 users and of the interfered system is 33 users. The channel separationhere was 3.225 MHz.

downlink direction. However, these assumptions can be justi-

fied by the fact that in those cases where the mobile is inter-

fering with the base station of another system, it is also exposed

to the downlink interference, which is, in that case, large com-pared to intrasystem interference. It has been also assumed that

the downlink power is constant since the common channels are

usually constant and at a relatively high level.

Figs. 6 9 show the capacity reduction as a function of

channel separation with and without the downlink power limi-

tation and with five and 15 IS-95 users per cell. The respective

adjacent channel interference ratio (ACIR) values are shown in

Fig. 5.

Results indicate that the capacity reduction is much larger in

microcells than in macrocells, as expected, since the minimum

coupling loss in microcells is usually much lower than in macro-

cells and blocking on downlink is not that effective. Results in-

Fig. 5. ACIR value as a function of channel separation computed based on theexample emission and filtering characteristics.

Fig. 6. Capacity reduction as a function of channel separation ( K = 1 5 );with the downlink power limitation.

dicates that the capacity reduction does not differ considerably

between two WCDMA macrocell layers with different site den-

sity of the IS-95 network.

When the downlink blocking has not been taken into account,

the uplinkinterference levels are higher and thus the capacity re-

duction is larger. The effect of the downlink blocking is affectedby the relationship of the uplink and the downlink ACIR. When

the downlink ACIR is much larger than the uplink ACIR, the

downlink blocking does not occur as often and has no effect on

the uplink interference. When the downlink ACIR is lower than

the uplink ACIR, the downlink blocking occurs more often and

removes those links that are very close to the base station of the

adjacent system. When comparing Figs. 6 and 7, we can see that

the capacity reduction in Case 4) decreases when the downlink

limitation has been considered. This is because in Case 4), the

maximum pathloss ratios were much higher than in Case 5), and

therefore the link specific limitation had more advantages in that

case.


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Fig. 7. Capacity reduction as a function of channel separation ( K = 1 5 );without the downlink power limitation.

Fig. 8. Capacity reduction as a function of channel separation ( K = 5 );with the downlink power limitation.

When comparing, for example, Figs. 6 and 8, we can see the

effect of IS-95 on the capacity reduction. In the case of Fig. 6,

there were 15 users, and in the case of Fig. 8, there were only

five users per cell in the IS-95 network. The difference results

indicate that with fewer users, the probability of high interfer-

ence is much lower.The results indicate that an ACIR of 40 dB or higher is

required in order to have lower than 10% capacity losses

in WCDMA microcells with the used IS-95 network sce-

nario. With the used filtering values, this would mean about

3.84.0 MHz channel separation between WCDMA and IS-95

carriers. In WCDMA macrocells, the situation is much better,

since the minimum coupling losses are larger. Already with

30-dB ACIR, the capacity reduction is at an acceptable level.

One has to remember that in the current case, these two

networks were planned independently from each other, so with

better planning, these capacity losses can be reduced consid-

erably. In the case of practical IS-95 planning, 625-kHz guard

Fig. 9. Capacity reduction as a function of channel separation (K = 5 );without the downlink power limitation.

bands between operators have been utilized, which should betaken into consideration when interpreting these results.

IV. CONCLUSIONS

The effect of the adjacent IS-95 network on the uplink ca-

pacity of the WCDMA is studied in this paper. A method for

computing the interference levels at the base stations also has

been presented. The analysis takes into account the interference

coupling between two CDMA systems due to SIR-based power

control. The effect of downlink blocking to the uplink interfer-

ence has been included into the model, as well. In the model, the

interference has been computed by using the pathloss difference

information. This information has been retrieved from pathlossmaps, which can be computed by using appropriate propaga-

tion models. In this paper, the OkumuraHata model has been

used in order to compute thepathloss maps forthe macrocellular

base stations and the ray-tracing propagation model in order to

compute the pathloss maps for the microcellular base station.

The developed method is independent of the used propagation

model. The effect of themodel is, however,essential, since espe-

cially in microcells the effects of close-by buildings and separa-

tion between line-of-sight and non-line-of-sight has to be taken

into account. The developed system model is applicable for var-

ious system simulation studies because of its fast computation,

relative simplicity, and possibility for usage of accurate prop-

agation data. The developed method can be utilized in varioussystem design, network dimensioning, and frequency planning

problems.

The capacity reduction case study shows that the network

structure has quite a big impact. This is because of very dif-

ferent radiowave propagation conditions in macro and micro-

cells. The macrocells are much more protected from the uplink

interference since the minimum coupling loss is large compared

to microcells. From the pathloss ratio distributions, it also can

be observed that the microcell users do not interfere the adjacent

system since the pathloss to the own base station is low. This

is because in microcells, the radiowave propagates through the

street canyons with rather low coupling loss.


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The capacity reduction is heavily dependent on the used

out-of-band emission as well as the received filter values.

The capacity reduction can be further decreased with a proper

balancing of uplink and downlink adjacent channel leakage

ratios. When the downlink ACIR is lower than the uplink ACIR,

the downlink will block those mobiles, which can cause high

interference in uplink direction. It must be taken into account

that the mask values used here were just example values andhave no realistic implementation background. This paper has

been concentrated on outdoor network cases. However, when

either system is deployed indoors, the nearfar ratios are even

worse than was shown in this macro/micro case, since the

minimum coupling losses are lower and the outdoor-to-indoor

pathlosses are higher.

REFERENCES

[1] J. Laiho, A. Wacker, and T. Novosad, Radio Natwork Planing and Op-timization for UMTS. New York: Wiley, 2001, p. 484.

[2] Y. Ishikawa and S. Onoe, Method for evaluating W-CDMA system ca-pacity considering adjacent channel interference, Electron. Lett., vol.35, no. 12, pp. 968969, 1999.

[3] K. Heiska, H. Posti, P. Muszynski, P. Aikio, J. Numminen, and M.Hmlinen, Capacity reduction of WCDMA downlink in the presenceof interference from adjacent narrow-band system, IEEE Trans. Veh.Technol., vol. 51, pp. 3751, Jan. 2002.

[4] K. Heiska, H. Posti, P. Muszynski, T. Rautiainen, and J. Numminen,WCDMA downlink coverage reduction due to adjacent channel inter-ference, Wireless Personal Commun., vol. 23, pp. 217242, Nov. 2002.

[5] K. Sipil, M. Jsberg, J. Laiho-Steffens, and A. Wacker, SHO gains ina fast power controlled WCDMA uplink, in Proc. VTC 1999 SpringConf., Houston, TX, May 1999, pp. 15941598.

[6] K. Sipil, J. Laiho-Steffens, A. Wacker, and M. Jsberg, Modeling theimpact of the fast power controll on the WCDMA uplink, in Proc. VTC1999 Spring Conf., Houston, TX, May 1999, pp. 12661270.

[7] K. Heiska and A. Kangas, Microcell propagation model for networkplanning, Proc. IEEE PIMRC96, vol. 16, pp. 148152, Oct. 1996.

[8] Y. Okumura, E. Ohmori, T. Kawano, and K. Fukuda, Field strength and

its variability in the VHF and UHF land mobile service, Review Elect.Commun. Lab., vol. 16, no. 9-10, pp. 825873, 1968.[9] M. Hata, Empirical formula for propagation loss in land mobile radio

services, IEEE Trans. Veh. Technol., vol. VT-29, pp. 317325, Aug.1980.

[10] J. Rajala, K. Sipil, and K. Heiska, Predicting in-building coverage formicro cells and small macro cells, in IEEE 49th Vehicular TechnologyConf. (VTC99), vol. 16-19, Houston, TX, May 1999, pp. 180184.

Kari Heiska was born in Toivakka, Finland, in 1968.He received the M.Sc. and Lic.Tech. degrees fromHelsinki University of Technology, Espoo, Finland,

in 1992 and 1996, respectively, and is currently pur-suing the Ph.D. degree.

Since 1994, he has been with Nokia Networksas a Research Engineer. His research interests areradiowave propagation, third-generation mobilesystem design, radio network planning, and opti-mization.

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Effect Adjacent Terhadap Kapasitas Uplink