[IEEE 2011 28th National Radio Science Conference (NRSC) - Cairo, Egypt (2011.04.26-2011.04.28)]...

28th NATIONAL RADIO SCIENCE CONFERENCE (NRSC 2011)

April 26-28, 2011, National Telecommunication Institute, Egypt

An Optimal Value of Multi-Threshold in the Bandwidth Reservation Scheme of

Integrated Services over Wireless Networks

Asmaa Saa/an #1, Hesham EIBadawy #2, Salwa Elramly *3

# Network Planning Department, National Telecommunication Institute * Electronics and Communication Engineering Department, Ain Shams University

Abstract Provisioning of guaranteed Quality of Service (QoS) in next generation cellular networks has become a great

challenge specially, when the wireless access networks have been used to deliver the multimedia services. Call

Admission Control (CAC) is one of the most important components of Radio Resource Management (RRM) that

affects the provided bandwidth utilization efficiency and QoS guarantees. In this paper, a multi-threshold

bandwidth reservation scheme is proposed to provide an acceptable solution for the trade-off between new call

blocking and handoff call dropping probabilities. The major objective of this paper is to find the optimal values of

the bandwidth thresholds'. In addition, the total cost function and loss probabilities were adopted to fulfill the

requirements of bandwidth management in wireless environments. The proposed scheme is modelled by

deploying a two-dimensional Markov process to evaluate the system performance. Throughout this work, a

detailed numerical investigation for the optimal thresholds is conducted.

Keywords: Call admission control; Handoff; Multi-threshold scheme; QoS.

I. INTRODUCTION

In recent years, wireless cellular networks have experienced great deployment and the demand continues to

grow, as different application requirements exist. The network offers integrated services such as voice, data, and video where mobile users communicate through radio spectrum of a base station. Due to the limited bandwidth/channel resources, efficient resource allocation strategies are crucial for meeting the Quality-ofService (QoS) requirements of multimedia applications. Call admission control is a widely adopted resource allocation strategy to limit the number of calls admitted into a wireless mobile network so as to reduce network congestion and maintain the QoS at an acceptable level. Simply stated, it is a mechanism that accepts a new call request provided if there are adequate free resources to meet the QoS requirements of the new call request without violating the committed QoS of already accepted calls. Dropping a call in progress is more annoying than blocking a new call request. Hence handoff calls are typically given higher priority. Since the operator would like to improve its delivered QoS. This is done via the reduction of the probability for a forced call termination, which can be achieved by insertion of guard channels or reserving a number of channels exclusively for handoffs in each base station (BS), lowering the handoff call forced termination probability. The remaining channels can be shared equally by both new and handoff calls, which we call the Guard Channel Scheme (GCS).

Guard channel schemes may be fixed (static), first introduced in [ 1, 2], or dynamic, such as in [3]. Some optimal solutions used to reduce the probability of terminating ongoing or handoff calls subject to different constraints have also been proposed in [4]. Fixed guard channel (FGC) technique reserve a certain number of channels a priori in each cell solely for the use of handoff calls, whilst dynamic guard channel (DGC) technique adaptively adjusts the proportion of channels reserved as guard channels according to traffic conditions. Thus, they react to change of call arrival rates in accordance with the changing traffic conditions at equal time intervals in every radio cell due to user's mobility. In addition, bandwidth can be dynamically allocated to the classes of traffic according to the traffic loading conditions with different classes.

In [2], a system with queues only for voice handoff calls is studied. However, all researches for bandwidth allocation are based on voice calls only or single-service whereas multiple traffic have not been considered.

One of the challenges in moving to a multi-service system is that the limited bandwidth has to be shared among multiple traffics. The Complete Sharing (CS) and Complete Partitioning (CP) schemes were investigated for two types of traffic, namely narrow-band and wideband.

In CS scheme, arriving traffic to a cell is accepted based on the number of available channels in the cell and the call admission control policy employed. Thus, users from different traffic types are allowed to share all available channels statistically. Under CS scheme, no distinction is made between new calls, and handoff calls for channel assignment. However, from subscriber's and regulation perspectives, abrupt termination of an ongoing call is



more unfavourable than getting a busy signal. Therefore, several policies with priority to handoff calls have been proposed. One of the priority-oriented policies that are quite known is the cut-off priority scheme [5]. Another policy that gives priority to handoff calls is the threshold priority policy [6]. Under this scheme, a handoff call is accepted as long as a channel is free. However, a new call is accepted only if the number of new calls in progress is less than a predefmed threshold and a free channel is available. Other prioritizing schemes allow either the handoff to be queued or new calls to be queued until new channels are obtained in the cell. The goal is to keep the handoff call forced termination probability close to a given target while constraining the new call blocking probability under a given threshold.

In CP scheme, a certain number of channels are reserved for certain traffic classes. In some cases a number of channels are designated to be used by multiple traffic classes. In [7], the authors proposed a movable-boundary scheme for voice and data traffic, in which bandwidth is divided into two sub-pools by two thresholds that can be dynamically adjusted. This scheme does not provide a service differentiation between new voice calls and handoff voice calls. Also voice and data traffic both require the same amount of bandwidth for service. In [8], the authors proposed a scheme which builds on the guard channel (GC) policy using two thresholds, referred to as the dualthreshold reservation (DTR) scheme, which uses one threshold to reserve channels for voice handoff, while the other is used to block data traffic into the network in order to preserve the voice performance in terms of handoff call forced termination and new call blocking probabilities. The difference between CS and CP is also discussed in this paper.

In [9], the authors proposed a model also built on the GC policy; however, it employs three thresholds, the first to reserve channels for voice handoff: the second to reserve channels for new voice calls and the third to reserve channels for handoff data sessions.

The main objective of the present paper is to find the optimum value of the three thresholds of the model used in [9] which is based on minimum total cost of the overall system and blocking probabilities for both of new voice, handoff voice, and both of new, and handoff data sessions. This is done in conjunction with the QoS guarantee a predetermined assured service level. The current model will help both of regulators and operators for best selections of the GC thresholds in correspondence to predetermined QoS level.

The paper is organized as follows. Section II presents the multi-threshold scheme and the model assumptions. Section III, describes the performance metrics of the proposed model which is used to evaluate the behaviour of the system. Section IV, illustrates the obtained results and its analysis. Finally, section V, concludes the presented work.

II. SYSTEM MODEL AND CALL ADMISSION CONTROL STRATEGY

A. Traffic Model and Assumptions

We consider a mobile wireless network with a cellular infrastructure. When a mobile moves across a cell boundary, a handoff call occurs. If there is insufficient bandwidth in the new cell that the mobile is moving into, the handoff could be forced terminated. For simplicity, consider a homogenous integrated voice and data mobile wireless network. Assuming FGC scheme, a set of N channels is permanently assigned to each cell. In such a homogenous system, we focus our attention on a single cell. The basic system model assumes that the new call origination rate is uniformly distributed over the entire mobile service area.

The system may have both stationary and mobile users. A fixed bandwidth, b, for data sessions is considered. Additionally, data sessions can tolerate some degree of service degradation; new data sessions and handoff data sessions are distinguished to accommodate the streaming class of data traffic. The system assumptions are in consistence with the previously published work in [9]. These assumptions may be summarized as follows, the arrivals of new voice calls and new data sessions are assumed to be Poisson distributed with the following arrival rates Anv and And respectively. As for the handoff voice calls and handoff data sessions, they are also assumed to be Poisson distributed with the rates: Ahv and Ahd-Thus, the total voice and data call arrival rates are:

Av = Anv + Ahv ( 1)

(2)

Call duration times or call holding times of voice and data are exponentially distributed with the average call duration time 11 f.Jvr and 11 f.Jdr respectively. In addition, the handoff voice and the handoff data are exponentially distributed with mean f.Jhv and f.Jhd:, respectively. This set of assumptions have been found reasonable as long as the number of mobiles is much larger than the number of channels in a cell [9]. Also, the following parameters are the rates for the related exponential inputs:



4V Jihv = JrR.J3 (3)

where, R represents the cell radius and V is the average velocity in a hexagonal shaped cell.

Thus, the total voice and data call service rates are:

Pv = Pvr + Phv

B. The Multi-Threshold Bandwidth Reservation Scheme

(4)

(5)

In the proposed multi-threshold bandwidth reservation scheme, N channels of each cell are divided into four regions by three thresholds NI, N2, and N3. It is assumed that NI, N2 and N are multiples of b, the number of channels needed to service a data call. These thresholds are adaptive according to the instantaneous cell traffic. Thus, we divide the whole time into equal length intervals. In each interval, the new call arrival rate is fixed at a certain rate, and it changes at the beginning or at the end of each interval. In each interval, the handoff arrival rate is predicted based on the new call arrival rate and the mobility parameters. To guarantee the target handoff voice call dropping probability and to maintain low call blocking probability, new data sessions can only use NI channels out of the total N channels; handoff data sessions can only use N2 out of the total N channels; and new voice calls can only use N3 channels out of the total N channels. However, the handoff voice calls can use up to N channels, thus handoff voice calls are only dropped when no channels are available in the cell as shown in Figure 1.

Incoming

m Tra c Am

Av

Av+ Ahd

Av+A.t

Hand off Voice Calls Only

N HandoffVoice Calls and New Voice Calls Only

N3 HandoffVoice Calls, New Voice Calls, and

Handoff Data Sessions Only

Nz

HandoffVoice Calls, New Voice Calls, Handoff

Data Sessions, and New Data Sessions Nt

Figure 1. Multi-threshold bandwidth reservation scheme.

Let i represents the number of voice calls in the system and j represents the number of data sessions in the system. The call admission policy can be summarized as follows:

• When a handoff voice call arrives, if (i+ 1) +jb 91, it will be accepted. Thus, a handoff call will only be forced terminated if there are no more channels available in the system.

• When a new voice call arrives, if (i+ 1) +jb 913, it will be accepted. Thus, a new voice call will only be blocked if this criterion is not met.

• When a handoff data call arrives, if i+ 0+ 1) b 912, it will be accepted. Thus, a handoff data session will only be forced terminated if this criterion is not met.

• When a new data call arrives, if i + 0+ 1)b 911, it will be accepted. Thus, a new data session will only be blocked if this criterion is not met.

The maximum number of new data sessions that can be in the system at any one instant is: h = N/ b and the maximum number of handoff data sessions that can be in the system at any one instant is: h= Nib, Also, the maximum number of data sessions (new and handoff) that can be in the system at any one instant as in [9].

We define the system state of a cell by the pair of the number of voice calls and data sessions in the system. Let i andj (O� i� N, 0 �j� Nib) denote the number of voice calls and data sessions in the system. Then, i andjb (0 g� N, 0 � jb� N2) represent the number of channels being used in the system by voice and data sessions respectively. Hence, the system state is defined as (i, j), where O� i� N, O�j� Nib, and 0�i+jb91. We formulate



our model as a two dimensional Markov process. Let P (i,j) be the steady state probability that there are i voice (new and handoft) calls and j data (voice and handoft) calls in the system. The transition rate and the balance equations of the multi-threshold bandwidth reservation scheme are shown in Figure 2.

Figure 2. State transition diagram.

All these sets of equations possess the following typical feature: there exists a subset of the state probabilities which we define as boundaries, and if the values of the boundaries are known, the recursive solution of the total system of equations can be carried out efficiently. There have been numerous techniques proposed to solve the type of balanced equations derived in [9]. In the current paper the equation is solved by using a recursive



technique developed in [10], which is based on the typical feature of Chapman-Kolmogoroff system of equations that there exists a subset of the state probabilities, called boundaries, and all other states can be expressed as a linear combination of boundary states. The main steps of this method are given in [10].

III. PERFORMANCE METRICS

All of the steady state probabilities P (i,j) can be determined by solving the boundary equations. Thus, The system performance measures such as new voice call blocking probability Pvb, the handoff voice call forced termination probability Pvd, the new data call blocking probability P db, and the handoff data call forced termination probability P dd can be derived as below:

N P"b = LP(i,j) (6)

i+jb?N3 N

Pdb = LP(i,j) (7) i+jb?N]

Pvd = LP(i,j) (8) i+jb=N

N Pdd = LP(i,j) (9)

i+jb?N2 These performance measures are greatly influenced by the selections of the threshold values of (Nj, N2, N3). In

order to evaluate how (N" N2, N3) values impact on the total system performance, we introduce factors y f3 and I I

a where 1> y > f3 > a . So, we can redefine (N" N2, N3) as follows:

Nl = y·N (10)

N2 =f3·N N3 =a·N

Then, we can introduce the system cost function as follows [11]:

cost _fonction =K(P"b +K2 'P"d +K3 ,Pdb +K4 ,Pdd

(11)

(12)

(13)

where Klo K2, K3, and K4 are weighting factors and Kj+ K2+ K3+ K4 = 1. As for weighting factors Klo K2, K3, and K4 they are chosen to privilege the voice or data call blocking probability according to the perspective of users.

IV. NUMERICAL RESULTS AND ANALYSIS

In this section, we started with dual threshold scheme and presented numerical results and compared it with the obtained results Dual Threshold Bandwidth Reservation (DTBR) in [8]. The system performance metrics considered in this validation are the handoff voice call dropping probability and voice call blocking probability. The following system parameters are in consistence with [8] which may be summarized as follows:

The total channel number N of each cell is set to be 30, Nj=N2=20 and N3=28 and the bandwidth requirement of data sessions b is set to be 2. The data call intensity Pd is set to be 7, with the average arrival rate of Ad = 0.007 S·I

and the average service rate of fld = 0.001 S·I. For voice call, the average service rate is assumed to be flv = 0.0083 S·I, while the voice call intensity Pv can vary from 6 to 16 when Ahv = O.4Av (i.e., higher user mobility). Figure 3 illustrates the comparison between the obtained results from the current model and those published in [8]. It can be seen that, these figures are approximately identical.



� �

/ ��

.................. .,../1 -'"

/ ..- �-:' . ;: - -

-- -:'- "'- ::-- - -

/ .. " ., ;:'", ..

F"- >

'" c � 0 CD Iii 10

-'

0

//: "..--�

'0 >

10-> /r"

--e--- New_V_ Prob_N1=20 N2=28 -8- Results of [81 DTBR N1 =20 N2=28 � - Handoff_V _ Prob_N1 =20 N2=28

- -)(- - Results of[81 DTBR N1 =20 N2=28

10";

6 8 10 12 14 16

Voice Traffic Intensity

Figure 3. New and handofJvoice call blocking/dropping probability vs. voice traffic intensity_

The next step introduces a comparison between dual threshold and multi-threshold schemes when the total channel number N of each cell is set to be 30, NJ = 14, N2=20 and N3=28 in the same conditions as in [8]. Figure 4 illustrates the performance of new and handoff voice call dropping probability_ The current comparison shows that the system performance is improved by using multi-threshold scheme. This may be resulting from limiting the allowable states for the data traffic which gives more and more priority to the voice traffic. In other words, the voice calls have much available states which leads to lower blocking probabilities and performance improvement.

w 10-1 ,---,---,----,----,----, c;; u � � .. - .. �-.... oS 1 0-> 1-.............................. + ................................. + .................................. ;j; .. ,. - - -

� i; ..

.c £. 10-.l � '"

-� -.. .... .. i 1....-

.................... t." •••••• • •• ••••••• • ••• ••••••••• 4

'co :

� // � � 10-' 1-7 .... / ..................... + ... / ............... , . .-'" 'j'" 00 0> c:

�

······· .. :r:::: /� 1 ... _ .......... _ . ......... J ...... ;;;.o-- .... --

.1--- A' -- '

65 10"

c;; u �

� Handoff(N1=14 N2=20 N3=28) -9- HandoffResults 01(8) (N1=20 N2=28 )

• �- New call (N1=14 N2=20 N3=28) '" z - -)(- - New call Results 01(8) (N1=20 N2=28 10� �--�=====C====�====�====�

6 10 12 14 16

Voice Traffic Intensity

Figure 4. Comparison between dual and multi-threshold in new and handofJ voice call blocking/dropping probability.

In the next part, we compared between dual threshold and multi-threshold bandwidth reservation schemes with the effect of cell radius when the total channel number N of each cell is set to be 30, NJ=14, N2=20 and N3=28 when the average data arrival rate of Ad = 0.007 s-

J and the average voice arrival rate of Av = 0.1 s-J and the velocity

V=30 kmIhr.



Figure 5 illustrates the performance of new and handoff voice call dropping probability. The obtained results show that there will be an increase in the blocking probability as the cell radius increases. In order to explain this phenomenon, due to the contention arising between the voice traffic enlargements when the cell radius is increasing, the service area will be enlarged. So it will introduce more voice traffic. This leads to an increase of the blocking probabilities.

� 10-2 r----,----,----,----r-----, Cii U � :g 10" -----:-------------�-----*- < o -"f- ::-: ::-��---t--- ��-� �-'�

: ok ' ' - : _ -0- - r - -<;-

10-9

• , ' , _+" ' : ' A -: :

---- -:-- - < --�--,-:-�-�- - ---- - -- ;- - -- - -- - ---- - :------- - -- - -:,' />r' : : -0-- Q- - B- -

, � / : AI'" - � - : " b- ' ---'_-e------,--/--.¥----- - --/- - ,---------- - ' - ---------- -:-- ----------, I, / ' , , , : I : : I / I I I

I I ' " I , I

,: ---;1-- - - - -- - --+- - ---------i-------------i-------- --- -

/ : i I , • , I r -

T -- - -- - -- - -- ' [ '- - -- - - - - -- - 1" --- - -- - -- -

T --- - -------

, , , , -e- Handol! failure for (multi- threshold)

-8- Handol! failure for(dual threshold) '"" - New Voice Call Blocking Probability(multi- threshold)

- -)( - - New Voice Call Blocking Probability(Dual threshold)

2 4 8 R (CeIIRadius)

10

Figure 5. Comparison between dual and multi-threshold in new and handoffvoice call blocking/dropping probability vs. cell radius

To fmd the minimum cost, let the weighing factors in equation 13 set to be K]=lO0I1221, K2=I000I1221, K3=11l1221, and K4=110/1221. This is reasonable as taken in [12]. Figures 6, 7 illustrate the change in the total cost with the variation of the factor fJ and how we can get the minimum cost and all of the blocking probabilities for constant y=0.25 and at a equal to 0.9 and 0.75.

1 10-1 r-----,---,---,----,---,-----,

:�(L � " '+",,<:., '-1"T"'" "" ___ :'::.' .. ' ..

.• ��=:=:j=�::;: . ..

.... " '.'::;' ."" .. �...... ..... -j "' � '� r ' . .. . .. , . .. �. . r�""'-.:.·i i:", .. , " ............ ,. . . . ,.! ......... ..... ............ :' ... '.: . �.:, ... : .... �

.

. .... . ... , . ,--

r.,.. l' ,1 �" ..... "' i " ",1

••••••••••• ... • ... ·"'C .. � .. ·i ··················:·:··:··f·�·

........ � �� .. "' "

<..;'

" ............ -- N=16 .. 1 -- N=20 ....................... :� .. .::: ..... ; .. .... .. .. .......... .... .... .. , . ...... " .. .... "" ..... ,;.;:,;. ..

-- "'-. ... _ . .., - - N=30

---- - N=40 a L-__ � ____ -L ____ -L ____ � ____ L-__ �

0.2 0.3 0.4 0.5

Beta (N2lN) 0.6 0.7

Figure 6. Cost function vs. fJ for a=0.9 and y=0.25

0.8



c:

� c: :::J

U.

'" 0 0

1 10.'

810.2

6 10.2

4 10.2

2 10.2

<� .. h-�. �+-------, l' i ' � ..... .... + ...... ... ....... ... ... .. ; ...... ............ ......... ; ..................... ..... ; ........................ . � .... ·

.. · ·

. . :�

.... T···· " , ,- ! � �. . . '''-'-<;' �� "'""':'< �i:/ 1,

................... ; "' .......... + . ..................... ....... ; ............................ + ........................... + ...... ... ................. � . "' , ' j " ' , '

'k [; .. ,. � f' �, , ' 1 .>.

-- N=16 -- N=20 - - N=30

......... N=40

;

"':- . , ....... ' t· ... � .

........ ·�:� · o .... ·.· i · · .......... · .......... ·+ · · · .......... · · -l

- � .... .

o �--�----�----�----�----�----� 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Beta (N2fN) Figure 7. Cost function vs. [J for 0.=0.75 and y=0.25

As shown in Figure 6, generally, as N increases, the blocking probabilities decrease due to the increase in the available resources. Hence, the cost function decreases. At N=16 and at fixed y and a., as N2 increases, data sessions forced termination blocking probability will decrease. However, this will affect the new voice blocking probability in the sense that it will increase. At low values of [J, the decrease in data sessions forced termination blocking probability is much higher than the increase in new voice blocking probability. So, the cost function

decreases. After certain value of [J, the decrease in data sessions forced termination blocking probability is lower than the increase in new voice blocking probability. So, the cost function increases again. Thus, there exists an optimum value of [J. At higher values ofN, the decrease of data sessions forced termination blocking probability is always much higher than the increase in new voice blocking probability. So, the cost function is always decreasing.

At N=16, comparing figures 6 and 7, we note that the minimum cost is lower in figure 6 than in figure 7. This is due to the fact that a. is lower in figure 7. This results in the fact that new voice call blocking probability will increase. This increase in new voice call blocking probability will increase the value of the minimum cost value.

v. CONCLUSION AND FUTURE WORK

In this paper, we proposed the multi-threshold bandwidth reservation scheme, which acts as an extension for the GC scheme. Performance measures are determined by modelling the system via a birth death process and solving recursively the linear equations derived from the Markov chain. The main contribution of the current paper is using the weighting factors to evaluate the system performance under multi-threshold reservation scheme. We found that when we choose the minimum cost which corresponds to certain weighting factors, this leads to minimizing the blocking probabilities and so improve the system performance. Numerical results show that guard channels for handoff calls can lower handoff blocking probability at the expense of new call blocking probabilities. However, the amount of guard channels to be reserved should be carefully selected. Excessive channel reservations may incur an unacceptably high level of new call blockings. This problem can be alleviated

by adjusting the weighting factors r ' f3 and a , that determines the reservation threshold N. Differently from the

previously published work, the current paper has presented an analytical model which not only has the ability to be more tractable, accurate, and stable but also it has other features. The obtained results show that there will be an increase in the blocking probability as the cell radius increases. This phenomenon arises due to the increase of the collected voice traffic as a result of enlarging cell coverage area. This leads to an increase of the blocking probabilities. The current work may be extended by including more key performance indices in the overall cost function such as, the mean weighting time, system expenses costs (capital & operational).

REFERENCES



[1] Theodore S. Rappaport., "Wireless Communications: Principles and Practice", Prentice Hall, Upper Saddle R iver, NJ, 1999.

[2] D. Hong and S. Rappaport, "Traffic modeling and performance analysis for cellular mobile radio telephone systems with prioritized and non-prioritized handoff procedures," IEEE Transactions on Vehicular Technology, vol. 35, pp. 77-92, 1986.

[3] Weimin Wu, Gan Liu, Guangxi Zhu, Xiaofeng Shen, and Youlin Ruan, "New stochastic control scheme for multiservices call admission in mobile wireless networks", Ln Proceedings of the IEEE 6th Circuits and Systems Symposium on Emerging Technologies: Frontiers of Mobile and Wireless Communication, 2004, volume 2, pages 545-548, May 2004.

[4] Mitchell K., and Sohraby K. (2001), "An Analysis of the Effects of Mobility on Bandwidth Allocation Strategies in Multi-Class Cellular Wireless Networks", IEEE INFOCOM '01, Vol.2, pp. 1075-1084.

[5] B. L i, C. L in and S. Chanson, "Analysis of a Hybrid Cutoff Priority Scheme for Multiple Classes of Traffic in Multimedia Wireless Networks," ACM/Baitzer Journal of Wireless Networks, Vol. 4, No. 4, pp 279-290, August 1998.

[6] B. Gavish and S. Sridhar, "Threshold priority policy for channel assignment in cellular networks," IEEE Transactions on Communications, vol. 46, no. 3, March 1997.

[7] Y.-R. Haung, Y. B. Lin, J. M. Ho, "Performance Analysis for Voice/Data Integration on a Finite-Buffer Mobile System," IEEE Transactions on Vehicular Technology, Vol. 49, No. 2, March, 2000.

[8] B. Li, L. Li, B. Li, and X. Cao, "On handoff performance for an integrated voiceldata cellular system," ACM W ireless Networks, vol. 9, pp. 393-402, 2003.

[9] S.E. Ogbonmwan, W. Li, "Multi-threshold bandwidth reservation scheme of an integrated voice/data wireless network", Computer Communications 29, Elsevier, 2006, ppI504-1515.

[10] U. Herzog, L. Woo and K. Chandy, "Solution of queuing problems by a recursive technique," IBM Journal of Research Development 19(3), 1975.

[11] Antonio Serrador and Luis M. Correia, "A Cost Function Model for CRRM over Heterogeneous Wireless Networks", Wireless Personal Communications, DOl: 10.1007/s11277-010-9919-5, January, 2010.

[12]Yaya Wei, Chuang Lin, Fengyuan Ren, Raad Raad, Eryk Dutkiewicz, "Dynamic Handoff Scheme in Differentiated QoS Wireless Multimedia Networks", Computer Communications Volume 27, Issue 1 0, 20 June 2004, Pages 1001-1011.

[IEEE 2011 28th National Radio Science Conference (NRSC) - Cairo, Egypt (2011.04.26-2011.04.28)]...

Documents

Transcript of [IEEE 2011 28th National Radio Science Conference (NRSC) - Cairo, Egypt (2011.04.26-2011.04.28)]...