Quality of service management efficient scheme for the ... · Quality of service management...

INGENIERÍA Investigación y Tecnología IX. 2. 113-129, 2008(artículo arbitrado)

Quality of service management efficient scheme for theuniversal mobile telecommunications system

Esquema eficiente de administración de la calidad de servicio para el sistema de telecomunicaciones móviles universales

E. Zaleta-Alejandre 1 , C.F. García-Hernández 2 , G. Cahue-Díaz 3 , J.A. Pérez-Díaz 4

and P. Sibaja-Terán 5 1 Centro Nacional de Investigación y Desarrollo Tecnológico–CENIDET, 2 Instituto de Investigaciones

Eléctricas–IIE, 3 Redes, Instalaciones y Servicios a Computadoras–RISC, 4 ITESM–Cuernavaca and 5 Universidad Autónoma de Cd. del Carmen-UNACAR

E-mails: [email protected], [email protected], [email protected],[email protected]

(Recibido: abril de 2006; aceptado: enero de 2007)

Abstract

This re search work pro poses a new Ra dio Re source Man age ment (RRM) scheme in or -

der to ac com plish the Qual ity of Ser vice (QoS) man age ment for the Uni ver sal Mo bile

Tele com mu ni ca tions Sys tem (UMTS). The so lu tion is based on UMTS stan dard iza tion

and a per for mance eval u a tion is pre sented to dem on strate its ef fi ciency.

Key words: Uni ver sal Mo bile Tele com mu ni ca tions Sys tem (UMTS), Ra dio Re source

Man age ment (RRM), Qual ity of Ser vice (QoS), Man age ment Scheme (3G), ser vice

class, Con nec tion Ad mis sion Con trol ler (CAC), Traf fic Clas si fier (TC), Ra dio Re source

Sched uler (RRS), Traf fic Dis patcher (TD), 3GPP, sim u la tion, ef fi ciency and con ges tion

con trol.

Resumen

Este trabajo de investigación propone un nuevo esquema Administrador de Recursos

de Radio (RRM), para llevar a cabo la administración de la Calidad de Servicio (QoS) en

el Sistema de Telecomunicaciones Móviles Universales (UMTS). El planteamiento de

solución que se presenta está basado en la estandarización de UMTS y se presenta

una evaluación de desempeño para demostrar su eficiencia.

Descriptores: Sistema de Telecomunicaciones Móviles Universales (UMTS), Admi-

nistración de Recursos de Radio (RRM), Calidad de Servicio (QoS), Esquema de

Administración (3G), clase de servicio, Controlador de Admisión de Conexión (CAC),

Clasificador de Tráfico (TC), Planificador de Recursos de Radio (RRS), Despachador de

Tráfico (TD), 3GPP, simulación, eficiencia y control de la congestión.

Intro duc tion

While the Second Generation (2G) cellular systems are capable of offering internet access, they do it in circuit mode, which represents enormous limita-tions not only in terms of the bit rate employed but

also in the resource use efficiency, since this typeof applications are known for generating informa-tion in bursts, which means that during a consi-derable time interval, the circuit is not used. Onone side, these limitations result in a reduced ca-pacity to offer this type of services, while on the

other hand, the connection cost for the users ishigher than the cost offered by a fixed network.Thenew broadband communications networks shouldbe capable of offering all kinds of multimediaservices. One of the most important requirementsto offer this type of services is that the networkguarantees, at the moment of establishing aconnection, certain parameters of QoS that shouldbe kept during the whole connection. In complextopology networks, like the ones used for mobilecommunications, it can be difficult to evaluate thequality parameters of the traffic in order to gua-rantee, for example: low delay, low jitter and lowpacket loss.

Particularly, the radio resources management is a function of special importance in the design ofthe Third Generation mobile communications sys-tems (3G). In this sense, there is the need of de-signing, studying and analyzing the distinct servicedisciplines that each base station of the networkmust have, while being able to guarantee that thecommunication link can comply with the establi-shed QoS criteria. This aspect will be essential tobe able to correctly design admission and con-gestion control strategies over the network, whichwill allow to maintain acceptably high values in theoverall system´s efficiency.

The UMTS system

Through a new terminal, the new mobile techno-logy will provide not only the voice communi-cations, but also the exchange of data and images. Basically, the 3G services combine the high datarate mobile access with the services based on theInternet Protocol (IP) [1]. The 3G mobile commu-

nication systems focus on offering a greater rangeof data rates than the present mobile communi-cations systems. For the deployment of an UMTSnetwork, different operation environments or sce-narios are considered, associated to different co-verage environments and types of mobility for theterminals. The target bit rates being offered to theusers depend on the environment, as shown in thetable 1 [2, 3]. It’s a fact that with greater areacoverage and faster mobile speed, the target bitrate becomes lower.

In this sense, figure 1 shows the different scenarios considered in UMTS (Huidoro) and (ETSI,1998),being the global coverage one of the main featuresin this new system.

QoS ASPECTS

Bearer services archi tec ture

The services support in UMTS is based on thehierarchical bearer services architecture defined in[4] and (Koodli et al., 2001). A bearer service isdefined as the medium through which the infor-mation is transmitted. This architecture considersthe decomposition in layers of the end-to-endservice offered to the user, taking into account thedifferent segments that are involved. Also this ar-chitecture is recurrent, so that the bearer servicesinside a layer are supported by the services offeredby the lower layers. This architecture is shown infigure 2.

From figure 2: Terminal Equipment (TE), MobileTerminal (MT), UMTS Terrestrial Radio Access Net-work (UTRAN), Core Network (CN), Interface be-

114 INGENIERIA Investigación y Tecnología FI-UNAM

Quality of service manage ment effi cient scheme for the universal mobile tele com mu ni ca tions ...

Table 1. Service targets in UMTS

Type of cell Environment Speed of mobiles Target bit rate

Macrocell rural outdoor High (up to 500 km/hr) 144 kbps

Macrocell urban/suburban outdoor Medium (up to 120 km/hr) 384 kbps

Macrocell low rangeIndoor/outdoor

Low (up to 10 km/hr) 2048 kbps

tween UTRAN and CN (Iu), Frequency DivisionDuplex (FDD), Time Division Duplex (TDD) and Ra-dio Access Bearer (RAB).

Service classes in UMTS

From the point of view of the QoS requirementsand fundamentally considering the delay tolerance

criteria, there have been four service classes inUMTS, from which the most prominent features are mentioned to continuation and are also more ex-tensively detailed in [4] and (García, 2002).

Vol.IX No.2 -abril-junio- 2008 115

E. Zaleta-A., C.F. García-H., G. Cahue-D., J.A. Pérez-D. and P. Sibaja-T.

Figure 1. Scenario for UMTS [3]

Figure 2. Quality of Service archi tec ture for UMTS [4]

Conversational class

The transmissions of this type are identified forbeing practically symmetrical and for requiring verysmall end to end transmission delays. The mostused application of the conversational class is thevoice service.

Streaming class

In this class, multimedia information is trans-ferred in unidirectional way so it can be processedlike a stable flow of data. Basically, this type ofapplication considers the transmission of video and audio sequences in real time.

Interactive class

They are services that in general present astrong asymmetry, since while the user of an endpoint is only sending small commands or requests, these ones unleash a much larger informationdownload. Examples of applications under this ca-tegory are: web navigation and database queries,as well as remote access to computers.

Background class

The e-mail, the short message sending and, the database information download or the remote mea-surements reading, are typical examples of appli-cations of this service class. The data transmissiondelay can be in the order of seconds, tens of se-conds or even minutes. Although the delay is nota restriction in these cases, the integrity of thedata is an indispensable requirement for theseconnections.

In general, the first two classes consider the socalled real time services, while the last two re-present the services which are not in real time.

QoS Attrib utes

In [2], some QoS requirement values are given asexamples of final applications. Nevertheless, these

requirements should be someway translated tovalues to be imposed in the different sections ofthe UMTS environment, since as it was previouslymentioned, in each section there is a correspon-ding bearer with different characteristics. In thissense, the definition of an attribute group can befound in [4], the definition of a set of attributes(parameters) can be found, as well as the margin ofvalues that these can take for the UMTS bearerservices and of radio access. The parameters (Dixit,2001) that have most impact in the QoS are:

– Residual bit error rate: indicates the quan-tity of bits erroneous inside the Service Data Units(SDUs) delivered, due to not detected errors.

– Erroneous SDU rate: is the fraction ofSDUs which are lost or detected as erroneous.

– Transfer delay: the SDU’s transfer delayis the time that elapses since its transfer request at the point of access, until it is received in the otherend. The Third Generation Partnership Project(3GPP) specifies the maximum values for the 95%of the delay distribution of the SDUs delivered. Thisattribute is defined only for the service classes inreal time.

Proposed scheme

The proposed scheme for the QoS management isshown in figure 3. Although the scheme was se-lected from diagrams found in the state of the art,the solution, the procedures and the criteria thatare implemented in this scheme, correspond to anew approach of solution (Zaleta, 2004). Themost important criteria in the selection of thescheme are:

– The decision to utilize the RRM schemeis supported mainly in the importance that theradio resources management has for the accesstechnology used in the new wideband networks.

– Another reason why the RRM was selec-ted in this work is because an important radio



resource project was found, in which a greatamount of information related to the topic is found. This work is called Advanced Radio ResourcesManagement for Wireless Services (ARROWS) pro-ject developed in the Technical University ofCatalunia (Arrows, 2001-2002).

– Also, in the ARROWS project, some stra-tegies for the QoS management that helped to give solution to RRM scheme, since at the beginningthe foundations to carry out the evaluation of thescheme were insufficient.

Therefore, the solution proposal is the following:

– To carry out the strategies implementa-tion for each element that conform the RRM. These strategies are given by solution algorithms.

–· With an IP packets generator as sourceof traffic, to obtain four files (each one representing one service class), which will serve like datapackets source for the simulation of the scheme(Castañeda, 2002) in MATLAB version 6.0.

– Evaluate the efficiency of the RRM con-sidering the three following clauses:

a) Maintain the RRM under stable conditions (this is, out of congestion the majority of the time).

b) Have the lowest packet loss rate possible, in function of the maximum delay permitted parameter, which will depend on the logic implemented in the Traffic Dis- patcher (TD).

c) Accept the highest quantity of users.

Connec tion Admis sion Controller (CAC)

The admission control strategy is considered in this element. The admission control strategy is imple-mented by an algorithm which determines if aconnection request should be accepted or rejected in function of the interference or load that thisconnection adds to the existing ones. Therefore it is responsible for deciding if a new Radio Bearer (RB)can be set-up. The considered admission controlmakes use of the load factor and the load in-crement estimation that is generated in the net-work radio by the connection request set-up. In the case that the load factor h is estimated in sta-tistical terms and assuming that they have k users



Figure 3. Radio Resource Magnagement (RRM) (Moustafa et al., 2002)

admitted in the system, the user k+1 should verifythe equation (1); (Sallent et al., 2003) and(Arrows-D09, 2002).

( )11

11

+

æ

èçç

ö

ø÷÷ ×

+

×

=

åfSF

E

Nr

i

ib

o i

i

k

n

(1)

+ +

æ

èçç

ö

ø÷÷ ×

+

£+

+ ×

+

=å( ) max1

1

1

1

1

1

fSF

E

Nr

k i

kb

o k

i

k

n

h

Where:

SFi is the Spreading Factor,

f the intercellular interference,

ni the activity factor of the traffic source,

r the coding rate,

hmax the threshold of admission control and

E

Nb

o

æ

èçç

ö

ø÷÷ the bit energy-to-noise density ratio.

Traffic Clas si fier (TC)

This element is the responsible of classifying thetraffic classes that are accepted into the RRM. Thetraffic is divided into four different types of service

(conversational, streaming, interactive and back-ground). Once the traffic (packets) is classified, issent through buffers to the TD. Thus the classifiedtraffic gives us the possibility to differentiate eachone of them, considering that its characteristics are not the same and to be able to give priorities inorder to dispatch. The Type of Service (TOS) field(Blake et al.) in the header of the IP packets isutilized for this process and contains a differentvalue for each class of service. In this work thetable 2 summarizes the values and characteristicsof this field. On the other hand, the quantity ofpackets that will be delivered depending ontransmission rate requested for each user isobtained with the equation (2).

Quantity of packets =

(2)Transmission rate Packets size inbits/ ( )

This procedure is applied for the four serviceclasses implemented in the RRM. Therefore, thequantity of packets delivered to the mobiles will bein function of the transmission rate requestedwithout caring of the type of service. The table 3shows the necessary quantity of packets in thedifferent transmission rates and packets sizeconsidered.



Table 2. TOS field values and char ac ter is tics

Service classes Binary value Hex valueTransmission

characteristicsPriority

Conversational 0 0 1 1 0 0 0 0 0C Minimum delay 4

Streaming 1 1 0 0 1 0 0 0 13 Maximum capacity 3

Interactive 0 1 0 0 0 0 0 0 02 Normal service 2

Background 1 0 0 0 0 1 0 0 21 Maximum reliability 1

Radio Resource Sched uler (RRS)

The congestion control strategy is considered inthis element. The congestion control algorithm in-cludes the following (Sallent et al., 2003):

1. - Congestion detection: some criteria shouldbe established to decide if the network is incongestion or not. The criterion to detect if thesystem has entered a situation of congestion iswhen the load factor is over a certain threshold ( )h h³ CD during a specific time period DTCD .

2. - Congestion resolution: certain actionsshould be carried out to recover the stability whenit is assumed that a congestion exists. Thecongestion resolution algorithm takes certainmeasures in order to try to solve these situations.Multiple possibilities exist at the moment ofcarrying out a resolution for the congestion, but ingeneral, three steps can be differentiated:prioritization, load reduction and load verification.

a) Prior i tiz a tion: in this case, traffic prioriti-zation is consid ered for the packets dispatch but not exactly to reduce the conges tion, although it helps to the stability and mainly avoids packetsto be discarded by exceeding its maximumpermitted delay.

b) Load reduc tion: It is carried out bymeans of not accepting any incoming connec -tion until the load level achieves certain per-mitted value. This being, the RRS will indi cate

the CAC not to accept any calls during a shortperiod of time because it is congested.

c) Load veri fi ca tion: after the step (b), theveri fi ca tion of the load consists on checking thefour buffers condi tion (one for each class ofservice) and to acti vate or deac ti vate the con-gestion control. If the conges tion persists, it isneces sary to return to (b). It is consid ered thatthe conges tion has been solved if the loadfactor is lower than certain threshold ( )h h³ CR

during a specific time interval DTCR .

3. – Congestion recovery: a step for congestionrecovery results necessary. This step consists ofaccepting calls again once the congestion hasbeen solved: at this time, the RRS will indicate tothe CAC that it can accept more calls.

On the other hand, the RRS will also be res-ponsible for monitoring the wireless channel statusin function of hBG (background noise that indicatesthe conditions of the wireless channel). This willserve so that the RRS reports to the TD about thechannel’s conditions allowing it to dispatch thepackets contained in the buffers. If the wirelesschannel’s conditions are adequate, the TD willdispatch the packets at the maximum dispatch ortransmission rate R

i allowed. Otherwise, the TD will

reduce the transmission velocity according to thevalue of hBG . If the channel’s bad conditions per-sist, the alternative is to not accept calls during a“very small period of time”, since not doing thiswould certainly cause a congestion. In this sense,



Table 3. Packets for considered trans mis sion rates

Transmission Packets size

rates 256 bytes 512 bytes 1024 bytes

64 kbps 31 packets 16 packets 8 packets




the minimum monitored noise by the RRS isobtained from the thermal noise power generalformula (Wayne, 1996) of the equation (3).

N KTBT = 10 10log ( ) (3)

Where:

NT is the thermal noise power in (dBW),

K the Boltzmann constant (1.38*10-23J/°K),

T the temperature (290 °K) and

B the bandwidth (5´106 Hz).

From calculation, we obtain:

NT =-136.98 dBW =-106.98 dBM,

being this value a reference for the maximumdispatch rate. Therefore, for a value of hBG moni-tored by the RRS, there is a corresponding value ofpackets to be dispatched.

Traffic Dispatcher (TD)

This element considers the following steps. Firstly,the part to calculate the background noise addedby a new connection and it is realized by theevaluation of the equation (4) which is obtainedfrom (Moustafa et al., 2002 and 2003), and sub-sequently, the part to execute the packet dispatch.Thus, this element is in charge of the buffer’spackets dispatch and, as it was mentioned before,the dispatch rate will be subject to the value of hBG

measured by the RRS.

hBG

bi i

i

b

o i

bj jj i

M

G p

R

E

N

W G P=æ

èçç

ö

ø÷÷

é

ë

êêêê

ù

û

úúúú

-¹å (4)

Where:

pi is the power level,

pj the power level as a function of the num-

ber of mobiles,

Gbi

the link losses,

Gbj the link losses as a function of the num-

ber of mobiles,

Ri the transmitted bit rate,

W the bandwidth,

M the number of mobiles and

hBG the background noise.

For the dispatch, a solu tion is presented inwhich the packet dispatch is consid ered under apriority scheme while the services work understricter delay char ac ter is tics, such as the conver -sa tional service which will have the greatest priority (first to be dispatched). On the oppo site, the back -ground service will be the one with the lowestpriority (last to be dispatched).

Thus, also the quantity of packets that will bedispatched for each class of service will be in func-tion to this priority; this means that for a certainquantity of dispatched packets, the 40% of thesewill be of conversational type, the 30% of strea-ming type, the 20% of interactive type and theremaining 10% of background type. The trans-mission delay is the main criteria considered forthis case.

Radio prop a ga tion model

The radio propagation model considered is theManhattan described in (Moustafa, 2001). For this model, the calculation of the path losses is ob-tained with the equation (5).

P R f RL K G K( ) . . log . log= + +142 37 29 74 50 37 (5)



Where:

PL is the path loss, RK the distance between mobile station and

base station in Km RK( . )0 05 3< < and

fG the central frequency in GHz fG( . )0 9 2< < .

Applying the equation (5), the path losses forthe three UMTS scenarios used for the calculationof hBG are:

- Picocell (0.1 Km): PL = Gbi = 100.970 dB.

- Microcell (1 Km): PL = Gbi = 151.160 dB.

- Macrocell (3 Km): PL = Gbi = 175.192 dB.

Param e ters to eval uate the effi ciency

The presented values are obtained in their greatmajority from the 3GPP specifications [5] and fromthe ARROWS project (2001-2002). The parame-ters considered for the different service classes arepresented in table 4, while in table 5 they are pre-sented by scenario.

Scheme eval u a tion

Param e ters based on the spec i fi ca tions

The simulations of the RRM scheme for the QoSmanagement were carried out in MATLAB version6.0 and the generated packets were obtained with



Table 4. Param e ters by service class

ParametersServices

Conversational Streaming Interactive Background

f 0.6 0.6 0.6 0.6

SFi

De 4 a 256 De 4 a 256 De 4 a 256 De 4 a 256

E

NdBb

o i

æ

èçç

ö

ø÷÷ ( ) 4.57 4.25 4.69 4.69

ni

0.67 0.57 0.47 0.37

r 1/3 1/3 1/3 1/3

R Kbpsi( ) 64, 144, 384 y 2048 64, 144, 384 y 2048 64, 144, 384 y 2048 64, 144, 384 y 2048

hCD(%) 0.8 0.8 0.8 0.8

hCR(%) 0.7 0.7 0.7 0.7

hmax 0.6 0.6 0.6 0.6

Table 5. Param e ters by scenario

ParametersScenario

Picocell Microcell Macrocell

p dBmi( ) 14 14 21

p dBmmax ( ) 21 21 21

R kmK( ) 0.1 1 3

f GHzG( ) 1.975 1.975 1.975

W(MHz) 5 5 5

the “Ultra Network Sniffer” Software (2002) [6].The obtained results are based on the represen-tation of the admission and congestion controlstrategies, while including the load behavior foreach service class.

In what the admission control concerns, theobtained graphics represent the admission effi-ciency to the RRM (user’s petitions against usersaccepted). At the congestion control, the load be-haviors at the different status considered by thisstrategy were obtained (out of congestion, stablestate and in congestion).

Finally, the load behavior for each service classshows how the strictest delay characteristic (con-versational) service class is kept with low valueswhen compared with the most delay tolerant ser-vice (background).

Next, the simulation results considering thetable 6 parameters were obtained, which served as base for finding the most adequate values for amore efficient scheme; this represents the impro-vement to the developed QoS management scheme.

The figure 4 shows the load behavior before thecongestion control strategy. As it is observed, the

congestion control is being applied correctly accor-ding to the steps that it should be following with the specified load value in the buffers. What is impor-tant to consider in this graphic is the time thatelapses between two states of congestion, sincewith the greater the time is, the better is the per-formance obtained. The time among congestion isdefined as the time that elapses between twoconsecutive states in which the congestion controlstrategy operates. It is important to recall that thecongestion control acts only when the load remains above the threshold hCD a time DTCD . This iscommented because as the figure shows the con-gestion control is not activated at every instant that the load surpasses the hco threshold.

Figure 5 shows the efficiency in the admissioncontrol. This efficiency is obtained from the userswho requested to enter the RRM (petitions) sche-me against that ones that were finally admitted.The restrictions to be able to access the schemeare: the parameters requested by the user (thesemust correspond with the transmission rate andscenario), the hmax threshold and at last, that thereare enough locations available for storing the packetsof the class of service requested. Therefore, whenthese restrictions have been verified and accom-plished, the user can access to the RRM. It is



Table 6. Considered foun da tion param e ters

Parameter Value

Separation between thresholds hCD and hCR 10%

Level of the congestion thresholds hCD 80%

Level of the out-of-congestion threshold hCR 70%

Time to activate the congestion control DTCD 3 sec.

Time to deactivate the congestion control DTCR 1 sec.

Admission threshold hmax 0.6

Spreading Factor SFi

256

Packet size 512 bytes

Time between dispatches 3 sec.

Length of each buffer 1000 localities

Simulation time 3 minutes

considered that in the case of none of the res-trictions being fulfilled, there should exist an optionin which the user could access to the RRM, this is,if for example a user requests a transmission ratethat cannot be supported, due to the fact that therequired resources do not exist, the CAC will offerhim a smaller rate and it will be a decision of themobile user to agree or to refuse to this availableresource. The sudden fall that both curves (peti-tions and accepted ones) suffer appears when thevalue of is obtained, in this moment the users de-cide randomly to remain connected or not. Afterthis process, it is possible to accept more usersagain.

The figure 6 shows the amount of users ad-mitted per class of service. Recalling that this is amatter of a random process, the amount of usersthat can be admitted to the RRM does not follow adefined pattern, this is, for a specific simulationthere can be more users admitted from the con-versational class than from any other class, while in a new simulation this preference can correspond to the background class of service.

Several simulations were carried out where thegreat majority of these presented an efficiencyvalue over 70%. Thus, from the graphic (see figure 5) that shows the admission control it is con-cluded that: the values of efficiency obtained areacceptable whenever they are maintained abovethe 70% of efficiency. In the following figures, the load behavior for the four classes of service isshown. Figure 7 shows the load for the back-ground service class and as it was mentionedbefore, the most important characteristic to con-sider in this service class is to maintain the dataintegrity without considering the transmissiondelay. It is because of this that the load remains in high values, which indicates that the packet de-livery is slow and in small quantities. It is nece-ssary to observe that even when it seems that insome of the graphics the maximum possible value of the load is reached, this does not happen,since that would indicate packets loss by overflowof the buffer.

Figure 8 presents the load for the interactive ser-vice class where, just as the background serviceclass, the data integrity is more important than thetransmission delay. Nonetheless, this figure showsa faster delivery of packets by presenting majorload changes and lower levels.

The figure 9 shows the load for the streaming

service class and this service class is not so strict in delay; nevertheless, it is necessary that the infor-mation is delivered in acceptable values. In thissense, it is possible to observe that the load leveldoes not reach the maximum and that its changesare major.

Finally, figure 10 presents the load of the con-

versational service class; this class of service is thestrictest in delay and therefore the one that shouldbe delivered to the users as soon as possible.Respect to this, it can be observed that duringmost of the time, the load levels are the lowest ofthe four classes of service. This is accomplishedthanks to the priority assigned to this service andalso to the bigger quantity of dispatched packets.

From the previous statement one concludes

that the lower the load values of the conversational service, the better QoS the users will perceive,whereas for the background service class, the most important thing is the information integrity. Be-sides, it highlights the importance that treating thetraffic in differentiated form has, since with this,one of the peculiarities from UMTS is solved, where a great number of applications are expected across service classes with its very own characteristics.

Best perfor mance param e ters

To be able to find an improved scheme it wasnecessary to run several simulations trying to findthe parameters that most impact in the behavior of the RRM. Therefore, the following simulations were ran:

1. Impact while changing the Spreading Fac-tor: SF=128 (reduced by half), Admission Control



Strategy = smaller amount of users (approximately 95).

2. Impact while changing the admission thre-shold: 0.95 (augmented), Admission Control Stra-tegy = bigger amount of users (approximately 300).

3. Impact while varying the separation per-centage between hCD and hCR thresholds: 20%(increased to double) = smaller number of timesentering congestion (time between congestions =48 seconds approximately).

4. Impact while changing the time betweendispatches (2 and 4 seconds): dispatches every 2seconds = congestion happens very few times (admission efficiency = 85% approximately); dispat-ches every 4 seconds = bigger number of times toenter in congestion (time between congestion =22 seconds approximately).

5. Impact while varying the level of the hCD

and hCR thresholds: 30% (superior), 20% (inferior), dispatches occurring every second = longer timesbetween congestions (56 seconds approximately)and bigger transmission efficiencies (91% appro-ximately).

6. Impact while changing the packet size(256 and 1024 bytes): 256 bytes (half) = noimpact (time between congestions = 33 secondsapproximately, 190 users approximately. And ad-mission efficiency = 77% approximately); 1024bytes (double) = admission efficiency increases(85% approximately).

The proposed values show themselves in table 7 (to compare them with table 6) and they are thosefor which a better behavior appears in the consi-dered strategies. The proposed values are basedon the analysis realized from the cases earlier ex-posed.

Figure 4 shows the congestion control strategy,where the load presents wider intervals betweencongestions as efficiency measurement for thisstrategy.

With regard to the admission efficiency, figure 5shows a value of 72.28%, which is greater than the 70% which is the reference value to establishwhether it complies or not with a good percentageof admitted users. In figure 6, the quantity of usersby service class can be observed (more users).



Table 7. Proposed param e ters for the best performance

Parameter Value

Separation between thresholds hCD and hCR 20%

Level of the congestion threshold hCD 80%

Level of the out-of-congestion threshold hCR 70%

Time to activate the congestion control DTCD 3 sec.

Time to deactivate the congestion control DTCR 1 sec.

Admission threshold hmax 0.95

Spreading Factor SFi

256

Packet size 512 bytes

Time between dispatches 3 sec.

Length of each buffer 1000 localities

Simulation time 3 minutes



Figure 4. Conges tion control strategy

Figure 5. Admis sion control strategy

Figure 6. Accepted users for class of service

In figure 7, the load behavior for the backgroundservice class is represented again. As it can beobserved, the proposed parameters do not affectthe behavior of the load, which continues to be infunction to the self characteristics of each of the

four service classes. In figure 8, the load behaviorof the interactive service class is shown, the strea-ming service class is shown in figure 9 and figure10 presents the conversational service class.



Figure 9. Streaming service

Figure 7. Back ground service

Figure 8. Inter ac tive service

Conclu sions

Nowadays, the internet and the mobile phone sys-tem receive the greatest interest inside the world of telecommunications, as shown by the great growth in the number of users that presently opt for usingthis type of services. In the particular case of theUMTS system, it is expected that for the year2010, 2,000 million mobile users will exist appro-ximately, which will be able to use this technologyin any part of the world according to figures re-ported by the UMTS Forum [3]. For this reason,these subjects are still under research worldwide.The following is concluded from this research work:

– The proposed scheme of Radio Re-source Management – RRM was implemented tomanage the QoS of the four different service clas-ses in UMTS, considering the parameters reportedin the specifications from the 3GPP.

– This RRM scheme presents a solution tothis crucial aspect of the new packet networks,with acceptable efficiency of user admission andwith a practical congestion control algorithm.

– The advantage that the differentiation ofthe services has, was made clear as a form of tra-ffic prioritization, this as an action from the TrafficClassifier - TC.

– The logic implemented at the traffic dis-patcher is based on the parameter of maximumauthorized delay.

– In the proposed RRM scheme, it waspossible to verify the impact that the SpreadingFactor has as the parameter that more reverbe-rates in the number of users that can be admittedinto the system.

Refer ences

[1] 3G. Infor ma tion related to the 3G systemsdevel op ment [in line]. Avail able in: http: //www.3g-generation.com

[2] 3GPP. Tech nical Spec i fi ca tion Group Servicesand System Aspects Service aspects; Servicesand Service Capa bil ities, (3G TS 22.105 version 3.10.0).

[3] UMTS Forum. Infor ma tion related to the UMTSsystem devel op ment [in line]. Avail able in: http:// www.umts-forum.org

[4] 3GPP. Tech nical Spec i fi ca tion Group Services and System Aspects; Quality of Service (QoS)concept and archi tec ture, (3G TS 23.107V3.9.0).

[5] 3rd Gener a tion Part ner ship Project (3GPP).Devel op ment of the stan dards and spec i fi ca -tions of the 3G networks [in line]. Avail able in: http: // www.3gpp.org.



Figure 10. Conver sa tional service

[6] Ultra Network Sniffer from GJPSoft. Powerfultool of network, Copy right 2002 GJPSoft Compu-ting Inc. [in line]. Avail able in: http://www.Gjpsoft.com/UltraNetSniffer

ARROWS-D09. First report on the eval u a tion ofRRM algo rithms by simu la tion. Tech nical Uni-versity.

ARROWS Project. Project devel oped for Tech nicalUniver sity Catalunia (UPC). Advanced radio re-source manage ment for wire less services(ARROWS), January 2001-December 2002, [inline]. Avail able in: http://www.arrows- ist.upc.es

Blake S. et al. An archi tec ture for differ en ti atedservices. RFC 2475, [in line]. Avail able in: http://www.ietf.org/rfc/rfc2475.txt

Castañeda-Trujillo O. Neural network based wire -less ATM sched uler for predicting and shapingVBR and ABR traf fics. MSc Thesis. CENIDET.2002.

Catalunia, Project partially financed for the Euro -pean Commis sion (IST 2000-25133), Barce -lona Spain, February 2002.

Dixit Sudhir et al. Resource manage ment andQuality of Service in Third-generation wire less

networks. IEEE Commu ni ca tions Maga zine, 39(2):125-133. February 2001.

ETSI, Euro pean Tele com mu ni ca tions Stan dardsInsti tute. Universal Mobile Tele com mu ni ca tionsSystem (UMTS); Selec tion proce dures for thechoice of radio trans mis sion tech nol o gies of the UMTS, [TR 101 112] V3.2.0, april 1998.

García-Hernando A.B. Tech niques of dimensionedand quality of service support for access net-works of UMTS mobile commu ni ca tions system. Doctoral Thesis. Madrid. Tech nical Univer sity Madrid. 2002.

Hernando J.M. Mobile commu ni ca tions of third generation UMTS, Mobile Tele phonic of Spain, 2000.

Huidoro J.M. UMTS the future of the mobilecommu ni ca tions [in line]. Avail able in: http://www.iies.es/teleco/publicac/

Koodli-Rajeev et al. Supporting packet-data QoS in next-generation cellular networks. EEE Commu-nications Maga zine, pp. 180-188. February2001.

Moustafa N.M. et al. QoS-Enabled broad bandmobile access to wire line networks. IEEECommu ni ca tions Maga zine, pp. 50-56, april2002.

Moustafa N.M. et al. Effi cient resource sched ulingin microcellular CDMA systems. VCT fall 2001Confer ence Proceed ings 2001, IEEE.

Sallent J.O. et al. Provi sioning multi media wire lessnetwork for better QoS: RRM strat e gies for 3GWCDMA. IEEE Commu ni ca tions Maga zine, pp.100-106, february 2003.

Wayne T. Elec tronic commu ni ca tions systems.Second edition. Prentice Hall. 1996. p. 496.

Zaleta-Alejandre E. Quality of Service manage ment effi cient scheme for the universal mobile tele -com mu ni ca tions system. MSc Thesis. CENIDET. 2004.



About the authors

Efraín Zaleta-Alejandre. Obtained his B.Sc. degree in elec tronics from The Tech nology Insti tute of Ciudad Madero,

Tamaulipas, Mexico in 1999, and his M.Sc degree in elec tronics in the area of Digital Systems with speci ality in Commu -

ni ca tions in the National Center of Research and Tech nology Devel op ment (CENIDET) in Cuernavaca, Morelos, Mexico in

2004. He has taken part in the National contest of creativity among the Tech nology Insti tutes in the field of Elec tronics.

From 1999 to 2001, he was professor in the Tech nology Insti tute of Tantoyuca, Veracruz, Mexico. He held diplomas in

the field of High Educa tion and Elec tronics. His research areas are networks and mobile commu ni ca tions.



About the authors

Carlos Felipe García-Hernández. Obtained his B.Sc. degree in commu ni ca tions and elec tronics from the Univer sity of

Guanajuato, México, in 1983 and his M.Sc. degree in tele com mu ni ca tions systems from the Univer sity of Essex,

England, in 1986. He has National and Inter na tional Publi ca tions, he has given Confer ences and advised several B.Sc.

and M.Sc. Theses. Also, he has attended Profes sional Training Courses in the U.S.A. and he gives Profes sional Courses in

México, B.Sc. Courses in ITESM Cuernavaca (Monterrey Tech no log ical Insti tute - Cuernavaca Campus) since 1996 and

Post grad uate Courses in CENIDET-SEP (National Center of Research and Tech no log ical Devel op ment - Public Educa tion

Bureau) since 1987. He works at the Elec tric Research Insti tute (IIE), Control and Instru men ta tion Depart ment, as a

Researcher and Project Manager on Radio Commu ni ca tions and Tele com mu ni ca tions since 1983 and He has been in

charge of several projects on Wire less and Mobile Networks. Further, He was a National Researcher Level-I (Pres i den tial

Appoint ment made to Outstanding Researchers) from 1987 to 1993, he is an IEEE Senior member, a CIGRE Corre -

sponding member and a CIME member (Mechan ical, Elec trical and Elec tronics Profes sional Engi neers Asso ci a tion).

Further more, he is a Profes sional Engi neer and a Tele com mu ni ca tions Consul tant, certi fied with regis tra tion No. 555

from the SCT (Tele com mu ni ca tions and Trans port Bureau) and the COFETEL (Federal Tele com mu ni ca tions Commis sion)

with the specialty on Radiocommunications since 1993 and therein he is also certi fied as a Class II Radio Amateur with

regis tra tion No. 10013 since 1999 with call-sign XE1RFG.

Guillermo Cahue-Díaz. Obtained his B.Sc. degree in Commu ni ca tions and Elec tronics with a special iza tion in Commu ni ca tion

from the National Poly technic Insti tute (1987). He got his M.Sc degree in Computer Science in the ITESM Campus

Cuernavaca (1984). He worked in the Computer Science Unit of the Elec tric Research Insti tute from 1978 to 1989

where he devel oped several projects related to computer networks and computers. He has worked in other enter prises

like: Networks and Tele com mu ni ca tions Services from the Condumex Group and Networks, Instal la tions and Computer

Services, in both compa nies, he has designed and installed data commu ni ca tion networks. He has been lecturer in

different National forums giving confer ences related to his speci ality field. He collab o rates with the CENIDET teaching in

the Elec tronics Depart ment since 1987, when he became the first prin cipal. He has super vised theses and designed

speci ality courses. He has become member of the Researchers National System and expert in teleinformatics regis tered

by the SCT. He is life member of the Mechanic and Elec tric Engi neer Asso ci a tion. He has been asso ciate professor in the

ITESM–Campus Cuernavaca. He has been asso ciate professor in the Univer sity La Salle in Cuernavaca since 1995.

Jesús Arturo Pérez-Díaz. Obtained his B.Sc. degree in Computer Science from the Auton o mous Univer sity of Aguascalientes

(1995). He worked as a system and network admin is trator in the Aguascalientes city hall. In 1997 he started his PhD

degree in the Univer sity of Oviedo, Spain. He studied the program New advances in Computer Science Systems, and

during these years he researched in mobile agents and published around 12 research papers in maga zines and inter na -

tional confer ences. During the same period of time he took part in a couple of Euro pean research projects and became a

full asso ciate member of the Euro pean founded research project AgentLink. He got his PhD Degree in Computer Science

in the Univer sity of Oviedo in 2000, after wards he became asso ciate professor of the Computer Science Depart ment in

the same Univer sity from 2000 to 2002. During these years he gave courses and made research in network and Internet

secu rity. Nowa days he is a researcher and professor in the ITESM–Campus Cuernavaca and member of the Researchers

National System, his research field focus in network secu rity and wire less commu ni ca tions. Currently has gotten the

recog nized Cisco certif i ca tions CCNA and CCAI, which allows him to give Cisco certif i ca tion courses. Addi tionally he is

giving courses on wire less commu ni ca tions and network secu rity in the post grad uate programs in the ITESM, also he has

super vised master and PhD theses in the same field. He has given secu rity courses in some Euro pean and South

American Univer sities.

Pedro Sibaja-Terán. Is a professor in the Engi neering Faculty at the Universidad Autónoma del Carmen, of Ciudad del

Carmen, Campeche, México. His research inter ests are focused on the area of coding for wire less chan nels, iter a tive

decoding and recon fig ur able hard ware for LDPC codes. At present He is a Ph. D. student at the Universidad Nacional

Autónoma de México (UNAM).

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