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A New Call Admission Control Scheme Using the User Conformityfor Non-uniform Wireless Systems*

Minhee Chot, Jae-Man Kim$,and Hyunsoo Yoont+Divisionof Computer ScienceDepartm ent of Electrical Engineering and Co mputer ScienceKorea Advanced Institute of Science and TechnologyE-mail: {mhcho,hyoon } @calab.kaist.ac.kr$Core Network Researc h Lab. L G Elec tronics Inc.

E-mail : aeman@1ge.com

Absfracf- Next generation wireless communication systems are ex-pected to satisfy quality of service (QoS) requirements by preventing calldroppings which are caused by user mobility. Call admission control(CAC) is becoming more important in guaranteeing the QoS of calls.Since existing CAC schemes estimate future requirements and reservebandwidth to guarantee a certain level of QoS, the bandwidth estimationmethod is very important in CAC schemes. Most conventional schemesuse the movem ent information of individual mobile terminals (MTs) to es-timate the bandwidth requirements. W hile these schemes estimate the fu-ture bandwidth usage relatively well, it requires high compu tational over-head and lots of memory space to keep and update the m ovement infor-mation of each mobile terminal, and therefore is hard to implement. Inthis study, we propose a call admission control scheme, which estimatesthe future handoffs using the handoff histories between BSs and the MTcorformify. The proposed scheme achieves low dropping ratio and highbandwidth utilization keeping low computational overhead. The perfor-mance of the proposed scheme is evaluated through simulations.

Keywords-Call adm ission control, quality of service, wireless system

I . INTRODUCTIONNext generation wireless communication systems are ex-pected to satisfy quality of service (QoS) requirements by pre-venting call dropping s which are cau sed by user mobility. Ca lladmission control (CAC) is becoming more important in guar-

anteeing the QoS of calls since m ore handoffs and m ore calldroppings will occur d ue to the sm aller cell size and increasedmultimedia applications in future wireless systems.Most CA C sche mes try to prevent call dropping s by reserv-ing channels which will serve handoff calls, and they reject callrequests if channels cannot be reserved. Sinc e existing CACschemes estimate future requirements and reserve bandwidthto guarantee a certain level of QoS, the bandwidth estimationmethod is very important in CAC schemes. Mo st conventionalschemes such as the Shadow Cluster [11 and the Most LikelyCluster [ 2 ] , etc. use the movement information of individ-ual mobile terminals (MTs) to estimate the bandwidth require-ments. W hile these schemes estimate the future bandwidth us-*This work was supported by the Korea Science and Engineering Founda-

tion (KOSE F) hrough the Advanced Information Technology Research Center(AITrc).

0-7803-7005-8/01/$10.000 2001 IEEE 1339

age relatively well, they require high com putational overheadand lots of memory space to keep and update the movementinformation of each mobile terminal, and therefore is hard toimplement.Recently, [3 ] proposed Collective Handoff Probability(CHP) ased call admission con trol strategy, which predicts fu-ture channel requests by using only handoff history data amongbase stations. This strategy assume s that some MT s have sim-ilar moveme nt characteristics collectively, due to the objec tssurrounding the cells such as roads, buildings, or highways.This scheme has the merit that it does not need any complexmethod to predict each users mobility and therefore has lowcomputational overhead. However, in real environments, whilesome users show the collectively similar pattern, there existother users that do not conform to the collective pattern. In theCHP strategy, these non-conforming users cause false hand-off prediction, and thus lead to unnecessary call droppings andbandwidth waste.In this study, we propose a call admission control scheme,which estimates the future handoffs using the information ofuser conformity. A user conformityreflects how strongly a userconforms to the collective handoff probabilities between BSs.Using this information, we can prevent unnecessary bandwidthreservation for non-conforming users and thus get the lowerdropping ratio and higher bandwidth utilization. The proposedscheme has low c omputational overhead because it is sim ple tokeep and update the value of user conformity for each user.The performance of the proposed scheme is evaluated byshowing the call dropping ratio and the bandwidth utilization.We compare the performance with two other schem es, the LO -CA L and the CHP scheme. In the LOCAL scheme, each basestation locally adjusts the amount of reservations needed toachieve the target dropping ratio. The simulation results showthat the proposed scheme achieves the lowest dropping ratioand the highest bandw idth utilization for all traffic load ranges.We also exam ine the effect of different methods for determ in-ing the value of user conformity.

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This paper is organized as follows. In Section 2, we describethe system model of the mobile system. In Section 3 , we pro-vide the simulation results to evaluate the performance of theproposed scheme. T he conclusion is presented in Section 4.11. SYSTEMMODEL

A. User Conformity ConceptIn [ 11 , the M T handoff probability w as defined as the prob-ability that an M T will leave the current cell to go into an ad-jacent cell, U J , given that it enters the cell from a different ad-jacent cell, U. Although in [ ] it is assumed that the m ovementinformation of specific MT, such as the velocity, direction an dcurrent location, can easily be obtained, it is know n that suchinformation is difficult to obtain in practice [4].we propose a call admission control scheme, which esti-mates the future handoffs using the inform ation of user confor-mity. A user Conformity eflects how strongly an M T conformsto the collective handoff probabilities between BSs. Using thisinformation, we can prevent unnecessary bandwidth reserva-

tion for non-conforming MT s and thus get the lowe r droppingratio and higher bandwidth utilization.The equations (1)-(3) show our handoff probability estima-tion, by which we estimate future bandwidth and perform calladmission control. Pi,j in equation (1 ) is defined as the proba-bility that an M T entering the current cell c from the adjacentcell i will leave the current cell to go into the adjacent cell j .

P0,j is the CHP for the MTs which originate in the current celland handoff to cell j . We also define the handoff history, H i , j ,as the number of MT s which have entered the current cell fromcell i and left the current cell for cell j during a time interval[T,,, - Th,Tcu,].T,,, is the current time and Th is the historycollecting duration. The future P,,j is estimated from Hi , j inequation ( I ) .

whe re is the previous value of Pi,j, N is the numb er ofneighboring cells, and a an d p are constants in [0,1].The user conformity f k and the collective handoff probabil-ity Pi,j are used for calculating Q i , j ( k ) n equation ( 2 ) . T hemore likely the MT k conforms to the collective handoff pat-tern, the large r value f k has. Pi , j (k ) ,he normaliz ed value of

Qi , j ( k ) n equation ( 3 ) is the handoff probability actually usedfor M T k . Pi,j k ) epresents the probability th at an M T k en -tering the current cell c from the adja cent cell i will leave thecurrent cell to g o into the adjacent cell j .

(3 )f k , the user conformity of MT k , is updated whenever M T

IC handoffs We propose two methods for updating the user con-formity.A.0.a User conformity update method I. In method I, f k isupdated as equation (4), where fk is the previous value of f kan d d is the incremenddecrement for fk as defined in equation( 5 ) . If the handoff direction of M T k conforms to t he collectivehandoff pa ttern, its conformity 6 increases by d. Otherwise,its conformity decreases by d. d has different values accordingto the level of conformity.

min(f; + d , 1)m a ( & - d ,0) in the conforming case,in the non-conforming casek = {81 if Ri , j 2 el (strongly conform )6 2 if 1 6 Ri , j < 01 (weakly conform)82 if 02 6 Ri,j < 1 (weakly unconform)61 if Ri , j < 02 (strongly unconform )

d = {Th e level of conformity is determin ed using the value of Ri,j

in equation (6). 1/N is the probability that an M T entering thecurrent cell from the adjace nt cell i will handoff to the adjacentcell j when all the handoffs between cells occur with the sam eprobability. Ri,j represents how high the collective handofftendency is. Ri,j 2 1 epres ents that the probability of handoffto cell j s larger than the average, while Ri,j < 1 means thetendency to ha ndoffs toward cell j is lower than the average.Assume the M T k entered the c urrent cell c from the adjacentcell i. When it moved to the adjacent cell j where Ri,j 2 1,the MT is said to conform to the collective handoff pattern andf k is increased. O n the contrary, f k is decreased when the M Tk moved to cell j with Ri,j < 1. Equation (5) shows fourconformity levels, where el and 02 (0, > 1 > 02 > 0) ar eused as thresholds to determine the conform ity levels. 81 an d6 2 (61 > 6 2 > 0) are incremen Mdecrernen ts for strongly andweakly conforming/unco nforming case, respectively.

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// Pseudo code for new call admissionI NewCallAdmit(B, z)2 begin345 begin67 If

if B + BE(t0)> BT then return falsefor dl t E [ to , o + Tma z]

if B ;t BE ( t )+BS(t)> BT thent o - 1C k = t O - H C s ( k ) + pE ( t )

t o - 1 > PQoSC k = t O - H ci(k)fC:=tO8 then return false9 endI I12 begin1314 end15 return true16 end NewCallAdmit// Pseudo code to check the bandwidth of neighboring cellsI CheckNeighborBandwidth(c, t l , 2 , B , p , s t e p, z)2 begin34 return false56 begin78 if

IO t i = t o + Tmin, 2 = t o + 2 T m a xfor each cell j E N C

if CheckNeighborBandwidth(c, t i , z , B , 0 ,j (z), 1,z) = false then return false

if BL ( t )+ B > BT for any t E [ t l , z ] he nfor all t E [ t l , z ]

if B + B i ( t )+ B: ( t )> BT thent o - 1C k = t O - H ci(k)+P

C k = t O - H c~(k))+c:=to; ( ' ) + Pt o - 1 > PQoS9 then return false10 endI 1 B!(t)+ = p . B f o r a l l t E [ t l , t 2 ]1312 t 3 = tl + Tmin, 4 = tl + 2Trnaxif s t e p < M A X S T E P and CheckNeighborBandwidth(j, t 3 , t 4 . B, ~ ! , ~ ( z )p , s t e p + I14 return true15 end CheckNeighborBandwidth

z ) =true for all k E Nj hen

Fig. 1. A detailed pseudo code for call admission control

A.0.b User conformity update method 11. In method 11 fk is B. CallAdmission Controlupdated as equ ation (7) , where f; is the previous value of fkan d T is the multiplier for updating f k as defined in equation(8). If the handoff direction of MT k conforms to the collectivehandoff pattern, its conformity fk increases by T . Otherwise,its conformity decreases by T . T has different values accordingto the level of conformity as equation (8), where y1 > 7 2 >1> 7 3 > 7 4 an d 41 > 1> 4 2 > 0.

71 if Ri,j 3 41 (strongly conform )7 2 if 1 < Ri,j < 41 (weakly conform)7 3 if 4 2 6 Ri,j < 1 (weaklyunconform)7 4 if Ri,j < 4 2 (strongly unconform )

(8 )- (

When there is a new call request with a bandwidth require-ment B in cell e, the proposed scheme entails the followingsteps:

Step 1: Step 1 tests whether adm itting this new call will stillmaintain the QoS of the cu rrent cell.Step 2-1: Ste p 2- 1 tests whether admitting this new call willstill maintain the QoS of the neighboring cells. N C s the setof neighboring cells of cell c. Then, if the neighboring cellsare estimated to be able to maintain their QoS, they reservebandwidth up to P ; , ~ ( X ) . B, where & ( E ) is the probabilitythat M T z originating in the current cell c will handoff to cell

j . Step 2-2: For each neighboring cell j of cell e , Step 2-2tests whether the QoS of cell j ' s neighboring cells is satisfied.Step 2-2 is repeated recursively up to the cells which are D,,,distant from cell c.Step 3: If all the cells that have been tested reply that there

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will be enou gh resources, requested bandwidths are reserved inthe cells and the new call is ad mitted to cell c.In Fig. 1, we address a detailed and self-contained pseudocode to describe the overall procedure for call admission con-trol and bandwidth reservation. The notations used in thepseudo code are as follows:t o is the current time. Tmin is the estimated minimumMT dwelling time and T,,, is the estimated maximum MTdwelling time. Bl ( t ) s the estimated used bandwidth of cell

c at time t , an d BF(t) is the reserved bandwidth of cell c attime t . BT is the total bandwidth of each cell. d,k(x)s theprobability that an M T 2 entering the current cell c from theadjacent cell i will handoff to the adjacent cell j . H is the timeduration for collecting handoff and call drop ping history. P Q ~ Sis the QoS threshold fo r call droppings. C i ( k ) s the number ofhandoffs at time k in cell c an d C: ( k ) s the number of droppedcalls at time k in cell c. d ( k ) s the handoff probability of acall entering cell j at time k .

111. P E R F O R M A N C EV A L U A T I O NA. Simulation EnvironmentThe simulation model is composed of 5 x 5 cells with wrap-around edge cells . Tw o types of MT s are assumed: a randomMT, which has the same handoff probabilities for all neigh-boring cells, and a regular MT, which hands off only to someparticular cells. A cell having only random M Ts is defined as anormal cell and a cell having both random and regular MTs asa regular cell. In Fig. 2, the cells on the horizontal and verticalroad are regular cells, and other cells are normal cells. Regularcells have a greater traffic load an d mo re handoff attempts thannormal cells because they deal with both normal and regularMTs.

Fig. 2. Simulation Environment

B. Simulation ParametersWe assume that new call requ ests follow a Poisson distribu-tion with variable mean arrival rates and that the holding tim e

of each call is exponentially distributed with a mean value of180s. The dwelling time for each M T is assumed to followa uniform distribution with the range of 40-60s. Three typesof calls are considered, namely, voice, aud io or video and theprobabilities of these types are 0.7, 0.2 and 0 .1, respectively.Each type of call has the following bandwidth requirements:voice = 1, audio = 4, and video = 8 (channels). Each BS ha s 40channels. T he ratio of the regular to random M T is 3:2.For comparison, we introduce two other schemes, the LO-CAL and the CH P schemes. In the LOCA L scheme, each BSlocally adjusts the amount of reservations needed to achievethe target drop ratio. Therefore in the LOCA L scheme, a BSincreases the reservation am oun t when the drop ratio is higherthan the target drop ratio, and vice versa. T he target drop ratiois 0.8% in these simulations. T he C HP scheme and the resultsfor regular cells are presented in [3]. The parameters for theCH P scheme and the proposed scheme are as follows: Th = 4s,a = 0.01, ,B = 0.01, Pmin = 0.10, D,,, = 2, Tmin= 40s, an dT,,, = 60s. In the conformity up date method I of the proposedscheme, O1 = 1.4, 02 = 0.6, 61 = 0.2, and 6 2 = 0.1. In the con-formity update method I1of the proposed scheme, 41 = 1.4,42= 0.6, y1 = 1.2,T~ = 1.1,y3= 0.9, an d 7 4 = 0.8.C. Simulation Results

Fig. 3shows the perform ance of dropping ratio against theoffered load for the schemes. The proposed sch eme achievesthe lowest dropping ratio for all traffic load ranges. The drop -ping ratio for the CHP and the proposed schemes decreasesfrom a certain traffic load, because, as the traffic load increases,the attempts of the CAC schemes to reserve bandwidth inneighboring cells fail more of ten, and traffic with larger band-width requirements is more often rejected. Therefore, becausemore bandwidth can be saved for handoff calls , the droppingratio decreases.

0.014

0.0120.01-5 0.00R

B 0.006s 0.0040.002

0 ' " " " " "0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.x 0.9 I

01tcrcd load

Fig. 3. Dropping probability vs . offered loadFig. 4shows the bandwidth utilization performance for the

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schemes. The proposed schem e achieves a higher bandwidthutilization than the LOCAL scheme and the CHP scheme. It isbecause the proposed sc heme estimates the handoff probabilityof M T more accurately w ith small overhead.35 0.45

0.40.350.3

B.70.60.50.40.30.2

Proposed B -+---.---.

Fig. 6. Bandwidth utilization vs. offered load

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 IOffered load

Fig. 4. Bandw idth utilization vs. offered loadFig. 5 shows the dropping ratio of the proposed A andthe proposed B schemes. Th e proposed A and the proposedB schemes update the user conformity using method I andmethod 11, respectively. The proposed B scheme achieveslower dropping ratio than the proposed A scheme. Fig. 6showsthe bandwidth utilization of the proposed A and the proposed Bscheme. Th e proposed B schem e provides a little higher band-width utilization than the proposed A scheme. Hence, we cansee that the update method I1 is more effective than the updatemethod I.

Proposedl B -*---0.0140.0120.01

0 0 0.1 0.2 0. 3 0.4 0.5 0.6 0.7 0.8 0.9 1Offercd loadFig. 5 . Dropping probability vs. offered load

IV. CONCLUSIONWe have proposed a new CA C scheme for wireless network

systems. The proposed scheme utilizes handoff informationbetween base stations and user conformity. A user Conformity

reflects how strongly a user con forms to the collective handoffprobabilities between BSs. Using this information, we can pre-vent unnecessary bandwidth reservation for non-conformingusers and thus get the lower dropping ratio and higher band-width utilization. The proposed schem e has low computationaloverhead because it is simple to keep and update the value ofuser conformity for each user. The performance of the pro-posed scheme is evaluated by showing the call dropping ratioand the bandwidth utilization. The sim ulation results show thatthe proposed scheme achieves the lowest dropping ratio and thehighest bandwidth utilization for all traffic load ranges.

REFERENCESD. A. Levine, I . F. Akyildiz, and M. Naghshineh, A Resource Estimationand Call Admission Algorithm for Wireless Multimedia Networks Usingthe Shadow Cluster Concept, IEEE Trunsactions on Networking, vol. 5 ,no . I , pp. 1-12, Fe b. 1997.A. Aljadhai and T. F. Znati, A Fram ework for Call Admission Control andQoS Support in Wireless Environments, in Pruc. IEEE INFOCOM99,Jae-Man Kim, Eui-Hoon Jeong and Jung-Wan Cho, Call Adm ission Con-trol for Non-uniform Traffic in Wireless Networks, Electronics Letters,vol. 36 , no. 1, pp. 96-97, Jan. 2000.C. Oliveira, J. B. Kim, and T. Suda, A n Adaptive Bandwidth ReservatoinScheme for High-spe ed Multimedia Wireless Networks, IEEE SAC , vol.16, no. 6, pp. 858-874, August 1998.

1999, pp. 1019-1026.

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