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A Fuzzy Cross-layer Method to Improve the Quality of Service in Uplink

Multimedia Transmissions in WiMAX

Amir Ghiasvand

Technical Manager

Bamdad ICT Group

Hamedan, [email protected]

Omid Ghiasvand, Zahra Moslehi

Computer Science ,Technical Manager

University of Wisconsin-Milwaukee, Bamdad ICT

Group

Milwaukee,USA,Hamedan, [email protected],[email protected]

Abstract WiMAX is a wireless standard that allows the

establishment of a broadband connection with high

throughput. IEEE802.16 provides high bandwidth and range,

while implementing and operating costs low, and as a serious

item to replace wired networks T1 and DSL is considered. On

the other hand we witness the important role of multimedia

applications in everyday human. In most multimedia

applications, quality of service plays a major role and boosting

this important parameter, increases the quality of multimedia

services. In this paper, a method which increases the quality of

service using Cross-layer mechanism with fuzzy decision tree is

presented. This method based on important parameters such

as quality of service delay, lost packets, timeout and also the

use of fuzzy decision tree, tries to improve quality of service in

WiMAX networks. Conducted simulation results indicate

significant influence of the proposed mechanism on improving

the quality of service, especially in the above parameters.

Keywords-component; WiMAX, Cross-layer, Fuzzy Logic,

Fuzzy decision tree, quality of service, multimedia

I. INTRODUCTIONIEEE Institute introduced a new standard in 2001, IEEE

802.16, that provides some broadband wireless access forbusiness use and local customer. This standard popularlycalled "Worldwide Interoperability for Microwave Access"or WiMAX. WiMAX design has the ability to provide QOSor quality of service. This standard can supports applicationand delay-sensitive services well. Since WiMAX is aconnection oriented standard, it can provide the QoS for eachconnection.

Today capabilities of multimedia transitions are veryimportant. For this purpose, IEEE 802.16 standard includesfeatures of the quality of service in order to supportmultimedia traffic with low delay. Features ofrequest/guarantee MAC layer in IEEE 802.16, ensure serviceguarantee levels such as T1, provide the best effort services,and also support cable level services. Moreover, themechanisms of QoS are available for customers in order tocreate and manage a special mechanism based on theirrequirements.

WiMAX also is the only network which is capable toprovide voice, video and data services. Moreover, it cansupport four services, voice, video, data, and mobility,

simultaneously on 802.16e in a network. All of theseservices mention as "IP Media Subsystem Services" or IMS.Generally, in transferring the multimedia streams such asVoIP over WiMAX, there are some concerns which the mostimportant one is voice quality (in VoIP) that is relateddirectly with the network quality of service.

Also the use of artificial intelligence techniques such asFuzzy logic can solve the problem of decision making inmany types of computer networks. So in this paper a fuzzydecision tree has been applied instead of classic decisiontree, to drop the difficulties of crisp cutting points in classicdecision tree.

II. INTRODUCTION TO WIMAX NETWORKSWireless Metropolitan network can be formed by StandardIEEE 802.16 that in it there is access ability to the

networks from the buildings through external antennaBS. WiMAX also is an alternative option for traditionalcable networks such as fiber optic connections and coaxial

systems using of cable modem lines and DSL.

WiMAX defines two layers of protocol stack, physical layer(PHY) and median access control (MAC). MAC

layer manages connections and security. PHY deals withcommunication and error correction signals in addition to

initial ranging, registration, bandwidth requests connection

channels for management, and data. Physical layer includesa sequence of frames with same length which are

transmitted by coding and modulation which are done by

RF signals. Physical and MAC frames are not locatednecessarily in above or below margins of higher layer.

Middle or interface mappings make the 802.16 standard

more flexible to support various traffics in transmissionsuch as IP, Ethernet, and ATM with high efficiency [1].

III. INTRODUCTION CROSS-LAYERIn traditional layered architecture, layers can only

communicate with its adjacent layers. This communicationhas been defined by Interfaces . By using Cross-layermechanism the structure of traditional layer model can bechanged and the network can be more efficient. Cross-layer

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mechanism changes the communication method. It makes aconnection between layers not adjacent [2] (Figure 1).

Layer architecture is a good idea that it should not bechanged, but this model has its own strategy and is notsuitable for designing next generation wireless networks [4].Therefore, Cross-layer mechanism tries to increasedefficiency of layer architecture by using some opportunitiesthat layer architecture provides.

Figure 1-Layer Model (Left) and Cross-layer (Right)

There is a misconception about Cross-layer. People oftenthink that Cross-layer is an alternative mechanism for layerconcept, while the mechanism is complement of layerconcept. The layer concept and Cross-layer mechanism aretools which must be used collaboratively to improve theefficiency and productivity in various types of wirelessnetworks [5]. The most application of Cross-layermechanism in wireless networks is to increase efficiency,

especially in multimedia stream transmission.

A. Architecture of Cross-layerArchitecture of cross-layer typically includes Nlayers and across-layer optimizer. The main task in Cross-layer

mechanism is done by cross-layer optimizer.Process ofoptimization is done in three stages, as follows [6] and [10] .

1. Layer abstraction: Computes an abstraction oflayer-specific parameters that are processed by the

optimizer.This process aims at reducing the overall data-

processing and communication overhead while

maintaining consistency.2. Optimization: Determines the values of layer

parameters that optimize a specific objective

function.3. Layer reconfiguration: Distributes the optimal

values of the abstracted parameters to the

corresponding layers, which in turn translate them

back into layer-specific information.

The three stages during the activity of a network are

repeated frequently, and they always try to create the best

performance for the network.

One layer is described by many parameters,but all theseparameters are not important for Cross-layer optimizer, so in

abstracting layer stage some parameters must be selected

which are crucial for Cross-layer optimizer and also do notincrease the cost of optimization[4].In a Cross-layermechanism different types of parameters can be defined [6].

directly tunable (DT) parameters that can bedirectly set as a result of the optimization process;

indirectly tunable (IT) parameters that may bemodified as a result of the setting of the DT

parameters;

descriptive (D) parameters that can only be readbut not tuned by the optimizer;

abstracted (A) parameters that are abstractions ofthe previous types of parameters.

In figure 2, architecture of cross-layer, interaction method

between three work stages, and how the above parametersmove in model are presented.

Figure 2-Architecture Cross-layer

IV. PROPOSED METHODCross-layerin WiMAXnetworkscan be implemented in

two parts: BSand SS.In this paper, we express and design a

Cross-layer mechanism which inBS part actives anuplinkcommunication.Proposed Cross-layer mechanism is

based on BS part and receives abstract information of layersprofile circumstances or conditions of channel, and QoS

parameters of a connection which is provided bytheMACandPHYlayers in the BS part (first stage of

architecture of Cross-layer).A special algorithm withrespect to this abstract information specifies appropriate

modulation or traffic rate separately for each connection

(second stage of architecture of Cross-layer).

Finally, the BS part should make aware the correspondinglayers from changes in the previous stage for re-

configuration (third stage of architecture of Cross-layer).

This procedure is shown in Figure 3.

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Figure 3- process optimization in BS part

A. Abstraction layer phaseIn this phase, BSneeds some information received signals

and SS conditions for establishing anuplink connection.Asuitable solution to this understand this information, is

thatSS send channel profile to BS.This sending is existedin standard IEEE 802.16and byChannel of Quality

Information Channel (CQICH) is possible.It is also possible

that BSusing a request message or Report Request (REP-

REQ) and its response or Report Response (REP-RES)which are provided by SS, measures the quality of channel

[3] [1]. CQICHalso can be sent periodically andsent by SS

once BS catches demandit. It containssome important

information about the conditions of channel andmodulation

methods in CINRreports [3] [1].

B. Optimization Cross-layerMain part of Cross-layer is the optimizer.Duty of BS part,which major activities are done in this section, includes

receiving abstract data of channel conditions, optimizingdata in order to improve quality of service, increasing

efficiency, and finally inform the corresponding layers of

the changes.

After optimization of operations information,BScaninform corresponding layers of changes such as changing

modulation and changing traffic rate.Optimizationprocedure is depicted in Figure 5.

Here changing the rate of traffic is changing coding

rate.For example, the traffic that is considered here is voice

variable traffic rate with AMRcodec which its coding ratecan be set by different amounts if necessary.For example,in the moments that conditions of channel are suitable,

channel can provide transition necessaries and high-speed

transfer of data up to 15Kbps. But when the channelconditions are not favorable, important parameters of

quality of service such as delay, packages loss rate, and

timeout is not in a situation to transfer data at high speedand to guarantee the delivery of packets, in order to remain

the quality for multimedia services in a desirable level the

rate of coding can be decreased andreaches 5Kbps evenlower.

The main algorithm presented BS part based on twoimportant parameters of quality of service: lost and delayed

packets.Both of these parameters are obtained from theabstract information of channel information that has been

described in section A.

The rate of lost packets error rate is obtained from sum of

packets error rate (for example, packages that are lost due to

channel error) and the rate is timeout packets.To calculatethe rates BS part should save up to date information of

channel conditions. Channel conditions can be obtained by

messagesREP-RSP, REP-RES, andCQICH which alreadyhave been described.Package error rateby BER diagram

onSNRin thePHYlayer are determined, and based ondiagram in figure 4 and order of position of modulationsthat is described in [7] decisions are made to change themodulation.

Figure 4-Diagram of BER on CINR

Due to packets loss rate if the rate is not acceptable two

cases will be studied:

a. First, do packets loss rate depend on the failure ofchannel conditions? If yes BS part

allowsMAClayer degrade the modulation.Thiscommand makes the model to be more powerful

against interference.

b. Second, do packets loss rate depend onunacceptable delay or timeout? This makes theother two cases:

I. Packets loss rate due to timeoutexclusively. This is because of the low

speed of channel, and it cannot transfer

data fast. In this moment BScan improvemodulation to increase speed and reducelosses due to the package Timeout.

II. In another case, a considerable percentageof failures depend on the channel

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conditions that are very poor.In this case,modulation must not be improved but the

traffic rate must be decreased in order to

adjust the packages loss rate.

On the other hand, when packages loss rate is very

low or not considerable BSpart can improve themodulation, due to increase the existing bandwidth, and itallows application layer to increase the traffic rate due to

improvement of main parameters of quality of service.

Finally the last two decisions must be specified that dependon average of delay rate of an active connection:

1. If the average delay rate is very low or negligible:In this case BS partcan request to increase traffic

rate in order to improve quality of serviceparameters.

2. If the average delay rate is not low and is in anacceptable range of delay: In this case BS

partcan improve the quality of service byenhancing modulation, due to increase data

transition speed and to decrease delay.

C. Layers ReconfigurationInteraction betweenSSandBS parts for exchangingmessages of increasing and decreasing the rate of delay can

be done by default management messages inMAClayer.

There are some reserved messages in MAC layer whichusing one of them adjustment messages of traffic rate can be

transfer. One of these messages is the message type of 67 in

bothIEEE 802.16andIEEE 802.16e. In [3] and [1] havebeen mentioned that this message is reserved for special usein future.

In table 1 the structure of this message is shown.

Management Message Type field, an 8-bit field, specifies

the number of management message. In this example, this

field is always 67. In this structure Direction field, 1-bit

field, specifies the direction of connection, zero

for Uplink connection and one for Downlink. Also Total

Rate Recommended field contains increasing or decreasingrequest of traffic rate.

Size Syntax

8bit Management Message Type

1bit Direction

32bit Total Rate RecommendedTable 1-structure of traffic rate messages [1,3]

Figure 5- the proposed decision tree for Cross-layer optimizer

V. FUZZY DECISION TREEIn this paper, instead of using the classical decision tree for

cross-layer optimizer (Figure 6) a fuzzy decision tree has

been used. In classical decision trees, cut points are Crisp.

Applications show that these trees are suitable only when

the classes have very specific boundaries, and they are

separate firmly. But in the real world there are classes thattheir borders cannot be separated easily. [8]

In fuzzy decision trees, some fuzzy rules are activesimultaneously from first of the tree till end of it, and finally

several (the number of tree leaves) conclusions will made.

The process of fuzzy decision trees is as same as process ofclassical decision trees, but instead of a crisp expression in

classical decision trees a fuzzy function is used, and the

value produced by it will be sent to the next step. The

difference between classical and fuzzy decision trees is

shown in Figure 6. Thus, in all parts of the leaves of fuzzydecision tree, final decisions, there are values that indicate

the degree of a decision. Finally, a leaf or a decision is

chosen that has the highest degree.

Figure 6-classical (Left) and fuzzy (Right) decision trees, and space of their

decision

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A. changing classical decision tree into fuzzyFor changing the classical decision tree in figure 6 into

fuzzy, following steps must be done

First in nodes that contain external inputs (inputmust be entered by the user), they must be

transform into a fuzzy value.To do this, for all ofinputs, a function must be made by fuzzy

probabilities then the value of input is passed

through this function, and its fuzzy value will be

received. For determining the fuzzy membership

function for external input nodes, following

formula is used:[9]

where n is the number of happened events x from

thetotal number of eventsN.

At this stage, intermediate nodes that are not leafnodes nor external inputs.In these nodes not onlythe function must be specified by the equation 1,

but also a fuzzy operator must be used to calculate

the output of the node combined with the value of

previews node.We have used "Minimum" fuzzyoperator for determining the output of this node.

The fuzzyMinoperator used here is:

(x) = Min ( (x1), (x2))

Where x 1 and x 2 are current and previews inputs

( (x1) and (x2) are fuzzy degrees of current node

input and output of previews node), respectively,and (x) is the output of current node.

Finally, for determining the values of leaf nodes ordecisions, there is no need to calculationoperations, because the value that has been passed

from previews node is the value of the current node

that is a leaf or a decision.

Figure 7- The changed decision tree into fuzzy. LR: packet loss rate, MP:

packet objection rate, DR: packet objection rate near to zero, D: delay, T:

time expiration of packages, T1: increase traffic rate, T2: Upgrade

modulation, T3: decay modulation, T4: Upgrad

The changed tree, in figure 5, into fuzzy decision tree is

shown in Figure 7.Also in figure 8 an example is presentedwhich includes the following inputs (values are changed

into fuzzy values by equation 1):

LR = 0.1, DR = 0.6, MP = 0.8, D = 0.9, T = 0.1.

After identification of input values, values of other nodes

are specified by the fuzzy operators.In figure 8 the valuethat is sent to the next step, is shown on the edge connected

to next node.Finally, the decision node that will be chosen,is nodeT3(decay modulation) which means it has thehighest degree (0.8).

Figure 8-An example of fuzzy decision tree

VI. SIMULATION AND RESULTSHere for reaching the specific goals of the paper, some

simulations carried out by NS simulator in addition to using

NSMiracle and WiMAX NIST.Simulation process first

starts with an SS and a BS parts which the number of SS

increases gradually (every 15 seconds), so at the end of the

simulation process for 1800 seconds the total number of SS

gets 100. For each of these SSs, a uplink voice connection

with AMR coding is created, and after connecting to the BS

part data exchange will be started.

Here, the measurements of some important parameters such

as packets loss rate, packets objection rate, and timeout rate,

will be compared and evaluated in two types, without and

with proposed cross-layer mechanism. These measurementswill be done for all connections. Also the presented resultsare acquired from the average results of the simulation that

is repeated for 8 times. In this data exchange, the PMP

topology is used. Moreover Bs is assumed as data source,and SS considered as data receiver.

Voice variable length trafficTraffic Type

QPSK, 16-QAM 64-QAMAccessiblemodulations

2 msLength of time

frame

100 MbpsTransfer rate

Table 2-Initial set of simulation

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In this simulation, available modulations in order to upgrade

or degrade are QPSK, 16-QAM and 64-QAM. Length ofTime frames assumed 10ms maximum data rate is

120Mbps. In figures10, 11, and 12 the results of simulationare presented.

Figure 9-Comparison of packets lost rate with (red) and without (blue)proposed method

Figure 10-Comparison of packets expiration rate with (red) and without

(blue) proposed method

Figure 11- Comparison of packets delay rate with (red) and without (blue)proposed method

As shown in figures 9, 10 and 11, the cross layer

mechanism could increase performance well, especially

with the many SSs. The most important reason for the

significant improvement proposed cross layer mechanism,

especially under many SSs, is the ability of proposed cross

layer to decrease the rate of timeouts , which is yielded byupgrading modulation so results in promotion of system

bandwidth.

VII. CONCLUSION AND FUTURE WORKSAs the simulation results show, the proposed cross layermechanism can improve the quality of service parameters

such as packets lost rate, Timeout packets rate, and also

decrease delay especially in heavy traffic and many number

of nodes significantly. But it seems that by using othermethods of implementation, this improvement of quality of

service can be studied. For instance, instead of fuzzy

decision tree an artificial neural network can be used.

Decision trees are decision making methods that are basedon model data, it mean that they do not need a lot of number

of data. But neural networks based on training and need a

lot of data to be trained. Except of this limitation accuracyof neural networks can be discussed for our next paper.

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