International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 1

ISSN 2229-5518

An Efficient Handoff Scheme for Multimedia

Traffic in OFDMA System

Manjusha Mangrulkar, Prof. C.N.Deshmukh

Abstract— The IEEE 802.16e Broadband Wireless Access (BWA) system is developed to cater for rapidly growing requirement for multimedia wireless services. Since the heterogeneous services provided by the system are connection-oriented, Call Admission Control and required resource reservation mechanisms are needed to achieve desired quality of service (QoS). Traditional admission control algorithms are based on bandwidth or channel reservation policy, which may be incompetent in IEEE 802.16e OFDMA systems for two reasons: (i) WiMAX system supports dynamic and flexible resource allocation, and (ii) there exists a fundamental tradeoff between bandwidth resource and power resource. In this paper, we propose an efficient call admission control scheme based on maximum use of subchannels using AMC to minimize the overall transmit power in OFDMA systems. Based on power reservation, we propose two power reservation schemes for inter-cell handoff calls and intra-cell handoff calls, respectively. Correspondingly, two reservation factors are introduced, the values of which are determined by optimizing the metric of Grade of Service (GoS). Computer simulation is carried out to evaluate the performance of the proposed call admission control scheme based on power reservation.

Index Terms— Call Admission Control (CAC), Call Blocking Probability (CBP), Call Dropping Probability (CDP), Broadband Wireless Access (BWA), OFDMA, IEEE 802.16e, Grade of Service (GoS)

—————————— ——————————

HE IEEE 802.16e broadband wireless mobile system based on OFDM(A) physical structure has been de- veloped recently, which is expected to support high- speed multimedia services applications for mobile sta- tions (MSs) moving at vehicular speeds [1], there is a growing interest in deploying multimedia services in mo- bile cellular networks (MCNs). Call Admission Control (CAC) is one of such areas in need of adaptation to ac- commodate multimedia traffic. The connection-level qual- ity of service (QoS) in MCNs is usually expressed in terms of call blocking probability and call dropping probability [2,3]. The call dropping probability is the probability that an accepted call will be forced to terminate before the completion of its service. According to [3],[4] the call dropping probability is directly proportional to the han- doff dropping probability which is the probability that a handoff attempt fails. A significant number of CAC schemes have been proposed during the last two decades. Because of the scarcity of bandwidth resource in wireless networks, the most prevalent approaches among them are the channel reservation schemes. These schemes can be classified into two categories: the traditional guard chan- nel schemes and the dynamic control schemes. The tradi- tional guard channel schemes reserve a fixed number of channels exclusively for handoff calls [5], [6], [7], which do not adapt to changes in the traffic pattern. The dy- namic control schemes make the admission decision in a distributed manner relying on status information ex- changing between adjacent cells [8], [9], [10].Typical CAC policies in wireline multiclass networks are complete sharing (CS), complete partitioning (CP) and threshold. In the CS policy, calls of every class share the bandwidth pool, in the CP policy, bandwidth for each class is exclu-

sively reserved, whereas in the threshold policy, a newly arriving call is blocked if the number of calls of each class is greater than or equal to a predefined threshold [11].

In this paper, we consider two kinds of handoffs: inter-cell handoff and intra-cell handoff. Inter-cell handoff is the process to maintain conversation continuity when a MS moves across the boundary between its serving cell and the destination cell to accept the handoff. Dropping occurs if there is no sufficient resource for the incoming handoff request in the target cell. Intra-cell handoff is a resource reassignment process due to channel condition degradation of an active call caused by terminal move- ment, during which additional resource is requested to maintain the QoS requirements and call may drop be- cause of resource insufficiency. In case of call drop during resource reassignment, one or more active calls have to be dropped according to a certain predefined criterion, which is out of the scope of this study. Considering the different characteristics of these two kinds of handoffs, two different power reservation strategies are proposed for them respectively, and for each strategy, a corre- sponding reservation factor is introduced. It is tradeoff between handoff dropping rate and call blocking rate; we determine the values of the reservation factors based on the optimization of the grade of service (GoS) perform- ance.

The rest of this paper is organized as follows Sec- tion 2 describes the system model for multimedia traffic of IEEE 802.16e. We present the framework for the effi- cient call admission control scheme to deal with real and non real time multimedia traffic in Section 3 The section 4 presents our power reservation-based admission control scheme for both inter handoff and intra handoff calls. In

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 2

ISSN 2229-5518

Section 5 the results and analysis in terms of the perform- ance evolution are discussed. Section 6 concludes this paper.

Consider an IEEE 802.16e cellular system consisting of 19 cells, with six cells in the first tier and twelve cells in the second tier (figure 1), surrounding the central cell. A sin- gle BS is located at each center of the cell, and the cell ra- dius is set to 1Km. The wraparound technique is used to eliminate boundary effect and MSs are uniformly distri- buted throughout the whole system topology.

8

Real-time services and non real time services are consi- dered in this paper, multiple classes and direction of calls are listed in TABLE 3 & TABLE 4 respectively.

TABLE 3

Traffic model of multimedia services

7 17 18 19

6

13 14 15 16

5

4 8 9 10 11 12

3

4 5 6 7

2

1 1 2 3

TABLE 4

Traffic model of direction

0

1 2 3 4 5 6 7 8 9 10 11

Fig 1: IEEE 802.16e cellular 19 Hexagonal Cells.

The centre frequency (*fc*) is 3.5GHz, and the total band- width in each cell (*Bt*) is 10MHz. The subcarriers of each logical subchannel are spread though the whole fre- quency band of that cell. The technique of adaptive modulation and coding (AMC) is used, thus the AMC scheme of each active call could be dynamically adjusted according the factors such as channel conditions and available radio resource. Information about the IEEE

802.16e OFDMA Parameters and specified AMC schemes are listed in TABLE 1 & TABLE 2 respectively.

TABLE 1

IEEE 802.16e OFDMA Parameters

TABLE 2

AMC levels in IEEE 802.16e

AMC lev- el | bit/s /Hz | AMC mode | SINR thrsh. (dB) |

————————————————

*Author - Manjusha Mangrulkar is currently pursuing masters degree program in Digital Electronic Engineering in Amravti University, India, PH -919820768641. E-mail: *manjusha.mangrulkar@gmail.com

*Co-Author Prof. C.N. Deshmukh is currently working as a Associate Professor in Prof. Ram Meghe Institute of Technology and Research, Badnera, SGB Amravti University, India,*

PH-0721575678. E-mail: cndesh1968@gmail.com

Path loss and shadow fading are taken into account in then propagation model, which is given by

PL (d) = PL (d0) + 10α log(d/d0) + χσ (1)

Where *d *is the transmitter-receiver separation distance; *d*0 is the reference distance, which is set to 30m; *α *is the path- loss exponent with the value of 3.5; *χσ *denotes the log- normal shadow fading, with a zero mean and a standard deviation of 8dB.

Considering the fact that admission control strategies are highly dependent on the resource allocation algorithms adopted in the system, an optimal admission control al- gorithm for multimedia system is proposed in this sec- tion. The optimization objective of this resource allocation problem is to minimize the overall transmit power of the BS while guarantee the data rate requirements of all us- ers.

Let *S *denote the total number of available sub-

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 3

ISSN 2229-5518

channels in a cell and *P *denote the maximum transmit power in the BS. Suppose there are *N *active calls in the cell at present, and the data rate requirement of the ith user is *DR*i (1 *≤ i≤ N*), the number of subchannels and the transmit power assigned to user *i *can be denoted by *Si *and *Pi*, respectively. If user *i*’s AMC level is set to *MCi*, the resulting data rate per unit of bandwidth from AMC level *MCi *can be denoted by *DR*(*MCi*), and the corres- ponding SINR are *f*(*MCi*) requirement, can be looked up in Table II.

Accordingly, the number of subchannels required by user

i is given by

Si=DRi/ (DR (MCi)*B0) (2)

where *B*0 denotes the bandwidth of each subchannel. The required transmit power on each subchannel of user *i *is

P_SC= (f(MCi)*(η+Ii))/Gi (3)

where *η *is the thermal noise assumed to be the same at each receiver, *Ii *denotes the co-channel interference per- ceived by user *i*, and *Gi *denotes the channel gain of the link from the BS to the *i*th user (i.e path loss). The re- quired power from the BS to user *i *is given by:

At first, each user is assigned the highest AMC level *Lmax *(according to Table II, *Lmax *= 6). Then, in each iteration, we try to reduce each user’s AMC level to the next lower level. Consequently, for user *i*, there will be an increment in subchannel requirement denoted by Δ*Si *and a decre- ment in transmit power requirement denoted by Δ*Pi*, thus a metric of unified power reduction can be defined as Δ*Pi/*ΔS*i*. The user with the largest unified power reduc- tion is selected to lower its AMC level, and gets the right to obtain additional subchannels. This iteration process continues until every user reaches the lowest AMC level *Lmin *or no subchannels are left unoccupied. The details of this algorithm can be described as follows:

1) Initialization: For each user *i*, initializes *MCi *= *Lmax*, the Corresponding subchannel and power requirements are given by

Si= [DRi/(DR(Lmax)*B0

Pi=Si*P_SCi

2) For each user *i *that satisfies *MCi > Lmin*, Calculate the required resource for the next lower AMC level:

The subchannel requirement increment and the power requirementdecrement are given by

ΔSi = − Si, and ΔPi = Pi –

3) Find user *i** with the largest unified power reduction:

Δ Δ

then, update the allocation information of the selected user *i**

= (DRi/(DR( ) B0)

= P_SC

4) Repeat step 2) and 3) until all users reach the lowest

AMC level or all the subchannels are assigned.

5) Check the assignment results.

Then allocation is finished successfully, else resource allocation is failed.

We develop an efficient call admission control scheme based on power reservation for handoff calls.

Let *Pcurrent *denote the reserved power for intra-cell

Handoff calls residing in current cell and

Let *Phandoff *inter-cell handoff calls moving into the

curent cell from its neighbor cells.

Then, the overall reserved power in the BS, *Poverall*, is

given by:

we have develop algorithm to determine Pcurrent and

Phandoff ,respectively.

To find an appropriate value of *Phandoff*, let’s first consid- er the average power and subchannel requirements for an inter-cell handoff call. Due to the bad channel condition on the edge of a cell, the AMC level assigned to an inter- cell handoff call is almost equal to *Lmin*. Thus, the aver- age number of subchannels that should be allocated to an

inter-cell handoff call can be given by *[DR/*(*DR*(*Lmin*) ・

B0)], and the corresponding average power requirement is

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 4

ISSN 2229-5518

where *DRaverage *denotes the average data rate require- ment, which can be determined from the data rate distri- bution presented in Section II. Since it is hard to predict the exact channel gain at the cell boundary, we use the average channel gain which is only determined by path loss in Eq.(1). Since no subchannels are reserved in our resource allocation strategy, some subchannels occupied by the ongoing calls in the current cell have to be reallo- cated to the handoff call by assigned an additional amount of power, *Phc *to the ongoing calls to make up for the loss in subchannel resource.

Let *P*s denote the total power requirements as *S *subchan- nels

and *P*s_averagel denote the power required *as *subchannels are occupied in all, according to the call admission control algorithm described in Section 3.

Then, the power gap can be given by

Phc = Ps_average − Ps (7) The total power reservation for inter-cell handoff calls is

given by:

where *K*(*K ≥ *0) is a reservation factor introduced for inter- cell handoff calls, which is related to the probability that inter-cell handoff occurs, as well as the degree of the tra- deoff between the call blocking probability and the drop probability. The optimal value of *K *will be decided later.

As the power reservation for intra-cell handoff calls is di- fficult to determine due to the arbitrary movement of the MSs, we propose the following method to get estimation. Let *Pcurrent [i]*denote the transmit power of the *i*th user from the BS determined by the allocation algorithm.

Let *Pboundary[i] *denote the required power to maintain its AMC level and subchannel requirement when user *i *reaches the cell edge. The power ratio at the edge of cell is *Pcurrent[i] / Pboundary [i]*. The smaller power ratio indi- cates a less probability of a user to reach the cell edge. Therefore, the approximate power reservation for user *i *in our scheme is described as

Accordingly, the total power reservation for intra-cell handoff calls is:

where *B *is a reservation factor introduced for intra-cell handoffs. Similar to *K*, the value of *B *should be carefully designed to balance between the call blocking probability and the drop probability.It should be noted that, although the reserved powers for the two kinds of handoff calls are determined separately, the overall reserved power *Pove-*

rall is shared by both inter-cell handoff calls and intra-cell handoff calls, because both kinds of handoff calls are on- going calls in the system, and should be treated with the same priority.

Since inadequate power reservation causes intolerable call drop probability while excessive reservation results in high call block probability, the metric of GoS is adopted to specify the degree of tradeoff between the call drop probability and the call block probability, which is given by

Herein, *Pdrop *(*λ*) and *Pblock*(λ) respectively denote the call drop probability and the call block probability under the call arrival rate λ, *α *is a weighting factor to describe the relative importance of *Pdrop*(*λ*) comparing to *Pblock*(*λ*), and a value of 10 is used in this paper.

Consequently, under a given call arrival rate, the two res- ervation factors, *K *and *B*, can be determined by solving the following two dimensional optimization problems:

(Kopt, Bopt) = arg min (10Pdrop + Pblock) (12)

B>0,K>0

Obviously, it is extremely complicated to yield an optimal

solution to the above problem. To reduce computational

complexity, we decompose this two dimensional optimi-

zation problem into two one dimensional subproblems,

and solve each subproblem separately to find the local optimal solutions, i.e., *K *and *B *then join them together to

be the suboptimal solution to the original problem in Eq. (12).

To determine *K *no power is reserved for intra-cell

handoff calls by setting *B *to zero, and the droppings

caused by intra-cell handoff calls are ignored, thus *Pdrop*

is replaced by *Pdrop_intra*, the dropping probability of

the inter-cell handoff calls. Therefore, the corresponding

one dimensional subproblem is formulated as follows:

K = arg min (10Pdrop_intra + Pblock) (13) K>0

Similarly, when determine *B *the overall reserved power

in a BS is equal to *Pcurrent *by setting *K *to zero, and the

drop calls of inter-cell handoff calls is not considered by

replacing *Pdrop *with *Pdrop_inter*, the probability of drop-

ping caused by intra-cell handoff calls. Thus, the second

one dimensional subproblem is formulated as

B= arg min (10Pdrop_inter + Pblock) (14)

B>0

Numerical simulation is utilized the above algorithm for call

blocking probability and call dropping probability for pro-

posed call admission control scheme and separate algorithm for intra-cell handoff and inter-cell handoff. Grade of Service

has of prome importance in the proposed algorithm.

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 5

ISSN 2229-5518

The performance of the proposed algorithm has been eva- luated by simulation in terms of Call block probability, Call drop probability and GoS with effect of various call arrival rate. We simulated IEEE 802.16e OFDMA cellular

each call arrival case, as K increases, the amount of re- served power increases, causing a reduction in the drop- ping probability and an increase in call blocking probabil- ity.

Inter Cell HandOff

network consisting of 19 cells, with six cells in the first tier

and twelve cells in the second tier (Fig.1), surrounding

the central cell. A single BS is located at each cell center, and the cell radius is set to 1Km. The wraparound tech-

nique is used to eliminate boundary effect and mobile stations are uniformly distributed throughout the whole system topology. The total number of subchannels in each cell is set to 1024, the overall transmit power of each BS is restricted to 100W and the thermal noise is -90dBm. We developed admission control scheme based on power reservation for handoff calls. Power is reserved for intra-

2.5

2

1.5

1

0.5

Lambda=0.1

Lambda=0.2

Lambda=0.3

cell handoff calls residing in current cell and inter-cell handoff calls moving into the current cell from its neigh- bor cells. Then, the overall reserved power in the BS is sum of reserved power for intra-cell handoff calls and inter-cell handoff calls.

K is a reservation factor introduced for inter-cell handoff calls, which is related to the probability that inter-cell handoff occurs, as well as the degree of the tradeoff be- tween the call blocking probability and the drop probabil- ity

Inter Cell HandOff

0

0 0.5 1 1.5 2

K

Fig. 3: Grad of Service **for **Multimedia traffic versus K

reservation factor for inter-cell handoff calls

The Grad of Service (GoS) performances versus K reser- vation factor for inter-cell handoff calls for 3 different call arrival rates for multimedia traffic are presented in Fig.

15. It is seen that a GoS curve versus K is always convex,

because either deficient or excessive amount of reserva-

tion will lead to a poor GoS performance. A minimum

GoS which corresponds to K can be found for each call

arrival case. For call arrival rate 0.1, 0.2 and 0.3, the corre-

sponding K are all equal to 1.5 for multimedia traffic.

0.7

Block Prob(Lambda=0.1) Block Prob(Lambda=0.2)

Inter Cell HandOff for Class 1 Traffic

0.6 __ __ Block Prob(Lambda=0.3) Drop Prob(Lambda=0.1)

0.9

Block Prob(Lambda=0.1)

0.5

0.4

Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

0.8

0.7

0.6

Block Prob(Lambda=0.2) Block Prob(Lambda=0.3) Drop Prob(Lambda=0.1) Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

0.3

0.5

0.2

0.4

0.1

0

0 0.5 1 1.5 2

K

0.3

0.2

0.1

0

Fig. 2: Blocking and Dropping probability for Multimedia

traffic versus K reservation factor for inter-cell handoff calls

Fig. 2. plots the call blocking probability and the call dropping probability of inter-cell handoff calls plotted against K reservation factor for inter-cell handoff calls at

3 different call arrival rate for multimedia traffic. In the simulation, we ignore intra-cell handoffs and set B=0. In

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

K

Fig. 4: Blocking and Dropping probability for Class 1 traffic versus K reservation factor for inter-cell handoff calls

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 6

ISSN 2229-5518

3

2.5

Inter Cell HandOff for class 1 Traffic

Lambda=0.1

Lambda=0.2

Lambda=0.3

3

2.5

Inter Cell HandOff for Class 2 Traffic

Lambda=0.1

Lambda=0.2

Lambda=0.3

2

2

1.5

1.5

1

1 0.5

0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

K

0

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

K

Fig. 5: Grad of Service **for **Class 1 traffic versus K reservation factor for inter-cell handoff calls

Fig. 7: Grad of Service for Class 2 traffic versus K reserva- tion factor for inter-cell handoff calls

0.9

0.8

Inter Cell HandOff for Class 2 Traffic

Block Prob(Lambda=0.1) Block Prob(Lambda=0.2)

Block Prob(Lambda=0.3)

0.8

0.7

Inter Cell HandOff for Class 3 Traffic

Block Prob(Lambda=0.1) Block Prob(Lambda=0.2) Block Prob(Lambda=0.3)

0.7

0.6

Drop Prob(Lambda=0.1) Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

Drop Prob(Lambda=0.1)

0.6 __ __Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

0.5

0.5

0.4

0.3

0.2

0.4

0.3

0.2

0.1

0

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

K

0.1

0

0 0.5 1 1.5 2

K

Fig. 8: Blocking and Dropping probability for Class 3 traffic versus K reservation factor for inter-cell handoff calls

Fig. 6: Blocking and Dropping probability for Class 2 traffic

versus K reservation factor for inter-cell handoff calls

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 7

ISSN 2229-5518

4

3.5

Inter Cell HandOff for Class 3 Traffic

Lambda=0.1

Lambda=0.2

Lambda=0.3

reserved power increases, causing a reduction in intra-cell handoff dropping probability and an increment in call blocking probability.

Intra Cell HandOff for Multimedia Traffic

3.5

Lambda=0.1

3 Lambda=0.2

Lambda=0.3

3

2.5

2.5

2

2

1.5

1

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

K

1.5

Fig. 9: Grad of Service for Class 3 traffic versus K reserva- tion factor for inter-cell handoff calls

B is a reservation factor introduced for intra-cell handoff calls, which is related to the probability that intra-cell handoff occurs, as well as the degree of the tradeoff be- tween the call blocking probability and the drop probabil- ity.

Intra Cell HandOff for Multimedia Traffic

1

0.9

0.8

0.7

1

0 0.05 0.1 0.15 0.2 0.25

B

Fig.11: Grad of Service **for **Multimedia traffic versus B reser- vation factor for intra-cell handoff calls

The Grad of Service (GoS) performances versus B reserva- tion factor for intra-cell handoff calls for 3 different call arrival rate for multimedia traffic are presented in Fig. 11. It is seen that a GoS curve versus B is always convex, be- cause either deficient or excessive amount of reservation will lead to a poor GoS performance. A minimum GoS which corresponds to B can be found for each call arrival case. For call arrival rate 0.1,0.2 and 0.3, the correspond- ing B are all equal to 0.1, 0.15 and 0.25 for multimedia traffic.

0.6

0.5

0.4

0.3

0.2

0.1

0

Block Prob(Lambda=0.1) Block Prob(Lambda=0.2) Block Prob(Lambda=0.3) Drop Prob(Lambda=0.1) Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

0 0.05 0.1 0.15 0.2 0.25

B

1

0.9

0.8

0.7

0.6

0.5

0.4

0.3

Intra Cell HandOff for Class 1 Traffic

Block Prob(Lambda=0.1) Block Prob(Lambda=0.2) Block Prob(Lambda=0.3) Drop Prob(Lambda=0.1) Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

Fig. 10: Blocking and Dropping probability for Multimedia traffic versus B reservation factor for intra-cell handoff calls

Fig. 10. plots the call blocking probability and the Dropping probability of intra-cell handoff calls at 3 dif- ferent call arrival rate for multimedia traffic versus B res- ervation factor for intra-cell handoff calls. In the simula- tion, we ignore inter-cell handoffs and set K=0. In each call arrival rate condition, as B increases, the amount of

0.2

0.1

0

0 0.05 0.1 0.15 0.2 0.25

B

Fig. 12: Blocking and Dropping probability for Class 1 traffic versus B reservation factor for intra-cell handoff calls

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 8

ISSN 2229-5518

5

4.5

Intra Cell HandOff for Class 1 Traffic

Lambda=0.1

Lambda=0.2

Lambda=0.3

3

2.5

Intra Cell HandOff for Class 2 Traffic

Lambda=0.1

Lambda=0.2

Lambda=0.3

4

2

3.5

3 1.5

2.5

1

2

1.5

0 0.05 0.1 0.15 0.2 0.25

B

0.5

0 0.05 0.1 0.15 0.2 0.25

B

Fig. 13: Grad of Service for Class 1 traffic versus B reserva- tion factor for intra-cell handoff calls

Intra Cell HandOff for Class 2 Traffic

1

0.9

Fig. 15: Grad of Service for Class 2 traffic versus B reserva- tion factor for intra-cell handoff calls

Intra Cell HandOff for Class 3 Traffic

0.7

Block Prob(Lambda=0.1) Block Prob(Lambda=0.2)

0.6 __ __ Block Prob(Lambda=0.3)

Drop Prob(Lambda=0.1)

0.8

0.7

0.6

0.5

0.4

Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

0.5

0.4

0.3

0.2

0.1

Block Prob(Lambda=0.1) Block Prob(Lambda=0.2) Block Prob(Lambda=0.3) Drop Prob(Lambda=0.1) Drop Prob(Lambda=0.2) Drop Prob(Lambda=0.3)

0.3

0.2

0.1

0

0 0.05 0.1 0.15 0.2 0.25

B

0

0 0.05 0.1 0.15 0.2 0.25

B

Fig. 14: Blocking and Dropping probability for Class 2 traffic versus B reservation factor for intra-cell handoff calls

Fig. 16: Blocking and Dropping probability for Class 3 traffic versus B reservation factor for intra-cell handoff calls

IJSER © 2011

International Journal of Scientific & Engineering Research Volume 2, Issue 8, August-2011. 9

ISSN 2229-5518

2.5

2

1.5

Intra Cell HandOff for Class 3 Traffic

Lambda=0.1

Lambda=0.2

Lambda=0.3

ing B are all equal to 0.1, 0.15 and 0.25 for multimedia traffic.

The author wish to thanks to dissertation guide, Prof. Chandrashekhar N. Deshmukh, under whose guidance, I learnt much more and completed successfully disserta- tion work most efficiently.

1

0.5

0

0 0.05 0.1 0.15 0.2 0.25

B

[1] Air Interface for Fixed Broadband Wireless Access Systems, IEEE

std. 802.16, 2004.

[ 2] Stephen S. Rappaport, ―The Multiple-Call Hand-off Problem in High-Capacity Cellular Communications Systems,‖ IEEE Transac- tions on Vehicular Technology, Vol. 40, NO. 3, pp. 546-557, Aug.

1991.

[3] Mahmoud Naghshineh and Mischa Schwarz, ―Distributed Call

Admission Control in Mobile/ Wireless Networks,‖ PIMRC ’95, pp.

289-293, 1995.

[4] Brocha Epstein and Mischa Schwarz, ―QoS Based Predictive

Admission Control for Multi-media Traffic,‖ 9-th Tyrrhenian Work-

Fig. 17: Grad of Service for Class 3 traffic versus B reserva- tion factor for intra-cell handoff calls

6 **C**ONCLUSION

It is anticipated that demands for multimedia services will grow in future wireless networks. Call Admission Control is essential for the efficient utilization of scarce radio bandwidth. In this paper, considering the support provided to multimedia service in IEEE802.16e standards, An Efficient Call Admission Control Scheme with power based Reservation for Multimedia Traffic is proposed for IEEE 802.16e network, based on maximum use of sub- channels using AMC to minimize the overall transmit power in OFDMA systems.

Traditional admission control schemes based on

channel reservation have a couple of shortcomings in WiMAX systems. Channel reservation is not fit for flexi- ble radio resource allocation and inevitably increase transmits power at BS. These problems can be well solved if power reservation is used instead of channel reserva- tion. In this paper, we have proposed an efficient call ad- mission control strategy based on power reservation. Two kinds of handoffs are considered: inter-cell handoff and intra cell handoff, and two reservation factors *K *and *B *are introduced, in order to balance the handoff call dropping rate and new call blocking rate. It is seen that from the result of GoS curve versus K & B, GoS curve is always convex, because either deficient or excessive amount of reservation will lead to a poor GoS performance. A mini- mum GoS which corresponds to K & B can be found for each call arrival rate. For call arrival rate 0.1,0.2 and 0.3, the corresponding K are all equal to 1.5 for multimedia traffic. For call arrival rate 0.1, 0.2 and 0.3, the correspond-

shop on Digital Communications, Lerici, Italy, Sep. 1997.

[5] M. Fang, I. Chlamtac, and Y.-B. Lin, ―Channel occupancy times and handoff rate for mobile computing and PCS networks‖, IEEE Trans. Comput., vol. 47, pp. 679–692, June 1998.

[6] R. Ramjee, R. Nagarajan, and D. Towsley, ―On optimal call admission control in cellular networks‖, in Proc. IEEE INFOCOM’96, pp. 43–50,1996.

[7] B. Epstein and M. Schwartz, ―Reservation strategies for multi-

media traffic in a wireless environment‖, in Proc. IEEE VTC’95, pp.

165–169, 1995.

[8] M. Naghshineh and M. Schwartz, ―Distributed call admission control in mobile/wireless networks‖, IEEE JSAC, Vol. 14, pp.

711–717, 1996.

[9] D. A. Levine, I. F. Akyildiz, and M. Naghshineh, ―A resource estimation and call admission algorithm for wireless multimedia networks using the shadow cluster concept‖, IEEE/ACM Trans. Networking, vol. 5, pp. 1–12, Feb. 1997.

[10] S. Wu, K. Y. M. Wong, and B. Li, ―A dynamic call admission

policy with precision QoS guarantee using stochastic control for mobile wireless networks‖, IEEE/ACM Trans. Networking, Vol. 10, pp. 257–271, 2002.

[11] Keith W. Ross and Danny H. K. Tsang, ―The Stochastic Knap-

sack Problem,‖ IEEE Transactions on Communications.

[12]―Power Reservation-based Admission Control Scheme for IEEE

802.16e OFDMA Systems‖ Chi Qin, Guanding Yu, Zhaoyang Zhang, Huiling Jia and Aiping Huang Institute of Information and Communication Engineering, Zhejiang University, Hangzhou

310027, China.

[13]Hassan Yaghoobi, ―Scalable OFDMA Physical Layer in IEEE

802.16 Wireless MAN‖, Intel Technology Journal, Volume 8, Issue 3,

2004.

[14] G. Yu, Z. Zhang, Y. Chen, and P. Qiu, ―An efficient resource allocation a6gorithm for OFDMA systems with multiple services‖, in Proc. IEEE Globecom’2006, 2006.

IJSER © 2011