QoS-based Policy for Call Admission Control in Mobile Cellular Network Marjan Bozinovski, Petar Popovski and Liljana Gavrilovska Institute of Telecommunications Faculty of Electrical Engineering Karpos I1 b.b., P.O.B. 574 91000 Skopje, R. Macedonia
[email protected], {petarp, liljana}@cerera.etf.ukim.edu.mk
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Abstract This paper proposes a QoS-based strategy for call admission in mobile cellular networks, based on the past system’s behavior. The algorithm is an extension of conventional guard scheme (CGC) and demonstrates improvements compared to CGC. It reduces the new call blocking probability, increases the total carried traffic and keeps the forced call termination probability almost unchanged. The proposed policy falls into the class of fractional guard policies. Each cell builds cumulative statistics from its “experience” and accepts a new call only when predetermined handoff failure probability is not exceeded. The generic form of the algorithm is independent of cellular network topology.
I. INTRODUCTION The mobile networks and supported services are tremendously growing. Introduction of microcellular networks leads to network capacity improvement, but it increases the expected rate of handoffs per call. As a consequence, some network performance parameters are affected, such as forced call termination probability. It is intuitively clear that termination of an ongoing call due to handoff failure is less desirable than new call blocking [l] [2]. Therefore, it is necessary to make a distinction between the blocking of new and handoff calls. The following performance parameters are relevant for the mobile cellular nctworks:
New Call Blocking Probability Pnb:This is the probability that a new call request is blocked. HandoflFailure Probability Phf: It is the probability that a handoff attempt is not successful because the destination cell has no free channel. Probability of Forced Call Termination Pfil:This is the probability that an ongoing call is forced to terminate before it completes the service. Actually, the forced call termination probability Pfil, is approximately a linear function of the handoff failure probability Phf[3]:
where, 1/p is the mean call holding time, and 1/q is the mean dwell time of the mobile user in a cell. 0 Carried Trafic T,: This metric represents the average number of ongoing calls per cell.
0-7803-6596-8/001$10.00 0 2000 IEEE
0 Network Capacity (Normalized to a single cell): It is the carried traffic per cell corresponding to the maximal offered traffic Tmuofiwhich satisfies the quality constraints PnW and of P n b and Pfil,respectively. In microcellular environment, the mean dwell time of mobiles with moderate speeds is much smaller than the mean can call holding time. Therefore, for small values of Phh Pfil be quite large. If the call admission policy treats both new is much larger and handoff calls in the same way, then Pfi, than both Pnband Phi [4].
It is obvious that a certain form of priority of handoff calls over new calls should be implemented in the mode of network operation. Several prioritization schemes were proposed and here we mention the most prominent ones: conventional guard scheme (CGC) [ 11, measurement-based queuing of handoff calls [5] or queuing of new calls when handoff calls are prioritized by means of guard channels [6]. CGC scheme is widely used due to its low implementation complexity and price. CGC works in the following way: if the total number of channels allocated to a cell is N, and the number of channels reserved for handoff calls is g, then a new call is accepted only if the number of free channels is greater than g. A handoff call is accepted if there is at least one free channel. It should be noted that here both N and g are integers. If the parameter Pfil is concerned, CGC gives very good performance, but the parameter Pnbis degraded to a great extent. The general implication of this is reduction of the carried traffic,.and hence, the network capacity. The application of fractional guard channel policy [7], where given channel is considered to be guard channel with probability less than one, refines the rigid CGC scheme. Or equivalently, fractional guard channel policy can be implemented by dynamic changes of the threshold that determines the number of guard channels. Our proposed scheme falls into the latter class of call admission policies. Its primary goal is to improve the parameter P n b of CGC, with insignificant affection of Pfil.The threshold of guard channels is determined on the basis of past operating “experience” of the system. This paper is organized as follows. Section I1 describes the simulation model used to examine these schemes. In section 111, the analytical expressions for evaluation of the performance parameters are given. Section IV describes the algorithm. Section V presents the simulation results and in section VI, we present the summary and concluding remarks.
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11. SIMULATION MODEL
The cellular topology considered in our model is based on Manhattan street environment assumptions (Fig. 1). It consists of n2 (n is integer) square blocks, which represent buildings, diyided by regular grid of streets. The block size is lOOxl00 m and streets are assumed to be with zero width. base stations As can be seen from Fig.1, there are placed at every street crossing. Cells are also square-shaped.
each cell is N. The nominal number of guard channels is denoted by g and this is the maximum value that can be obtained for guard channels. Depending on network behavior and the influence of proposed algorithm, the actual number of guard channels, at given instant, can be less than g . OF PERFORMANCE PARAMETERS 111. EVALUATION
In section 1, several parameters that reflect network performance were presented. The new call blocking probability and forced call termination probability are significant to the service users, while the service provider is concerned with the efficient usage of the resources, indicated by carried traffic per cell. The parameters of interest are evaluated as follows: 1) New call blocking probability ( Pnb) is defined as:
Pnb =
total number of blocked new calls in all cells total number of new call requests in all cells
2) Forced call termination probability
(P,,)can
be
obtained from: Fig. 1. Manhattan street model Pfc,
Each base station resides at the center of a particular cell and defines its radio coverage. Their size is also lOOx 100 m , so a cell covers half a block in all four directions. Thus defined cells are called halfsquare cells [8]. Although simple, Manhattan model is widely used [4] [lo], since it gives a relevant insight into network behavior. In this paper, only mobile-to-fixed calls are assumed. It is also assumed that the total number of mobile users in a cell (active and inactive), at any instant, is much larger than the number of ongoing calls (active users) in the same cell. Hence, the new call arrival process is taken to be Poisson, with constant average arrival rate. The service time of a call is assumed to be exponentially distributed, with mean value of 120 s. The edge effects, that emerge from abrupt truncation of the finite service area in the simulation, are partially eliminated by periodic assumptions about neighboring relations among the outermost cells. In that way, the service area logically represents a torus surface instead of a plane region. For example, if a user reaches the north-most edge of the city, he will re-enter the city from the south-most edge. It is natural that, in microcellular networks, handoff blocking is especially critical for fast moving users (highspeed vehicles). Therefore, truncated normally distributed speed (ve[O km/h, 100 km/h]) with mean and standard deviation equal to 30 km/h is assumed. The motion of vehicles is restricted along the streets. The mobile user turns at every junction with a probability of p=O.1 to the left or to the right. The channel allocation scheme assumed is fixed channel assignment (FCA). The total number of channels allocated to
=
total number of blocked handoff attempts in all cells total number of admitted new calls in all cells
3) Carried traffic per cell ('T ) is given by [4]: Tc
=
T
tdur I NCA
off tP
where Togis the offered traffic to the network normalized to a single cell. In fact, To,,= h / p where h is the average arrival rate, and p is the average call service rate. tdu,is a cumulative duratidn of all calls that were admitted in the whole network. NCA is the total number of new call attempts in all cells. t p is the mean service time and t,,= 1/p. td,,, and NCA are obtained as outputs from the simulation. Hence, the value td,,/NCA represents the eventual average duration of a call. Since some new calls are rejected, and some ongoing calls are terminated before completion of the service due to handoff failure, this value will be less than the mean call service time tp . Thus the quantity tdU,/NcA normalized to the mean call service time t,, gives the fraction (tdu,/NCA)/t,,of the offered traffic To,,,which is really carried by the network.
Iv. DESCRIPTION OF THE ALGORITHM This novel approach for call admission is based on dynamic approach and is adaptive in nature. Each cell continuously monitors the number of occupied channels within its area, as well as the total number of occupied channels in the neighboring cells. When the number of occupied channels in the observed cell is greater than (N-g) and when new call request is posed to the corresponding base station, it is not
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immediately rejected. There is still possibility to accept it for service, if such decision in the past had not forced handoff failure rate above given QoS criterion. The algorithm operates only on new calls, since hahdoff calls are accepted whenever there is a free channel in the destination cell. If we observe the cellular structure as a two dimensional array, each cell can be represented by row and column index. According to Fig.2, Cijdenotes the cell that is located at the intersection of i-th row and j-th column. Let the scalar N,(t) represent the number of active users (occupied channels) in the cell CUat the instant t. Let the other scalar, Aii(t) denote the total number of active users in the cells that are immediate neighbors to Cijat the time t. That is,
This is the probability that the handoff request will be rejected during the period to < t I to + T if at the moment t, the cell is in the state S,J(t,). Here, Tis taken to be the mean dwell time for an inactive mobile station, which is computed as a quotient of the half a cell length and the average speed. N is total number of channels allocated to a cell. It is important to note that the conditional probability defined with (3) depends on time and the state of a cell and is updated with every occurrence of new call request that finds that cell in that particular state. The value of (3) for S,(t,) at tois determined from previous occurrences of the same state. Let M denote the total number of occurrences prior to to when the cell had been in the same state S,J(to). Let K denote the number of such unsuccessful occurrences prior to to. Here, by "unsuccessful" we mean the occurrences when, T seconds after the observed instant, there had been at least one handoff failure. If W M I PWs,the new call is accepted, or else it is rejected. It is clear that the values of K and M are changing dynamically (and thus adaptively), since the occurrence at the observed moment will take place into the future estimations of conditional probability. In summary, the procedure (pseudo code) for new call admission can be presented as:
Fig.2. The cell Cij and its neighboring cells
IfN,(b)Pws. As we pointed out, the goal of the new strategy is: when g is fixed, to reduce the probability Pnb of implemented strategy relative to that of CGC, and to keep Pfi, of the new strategy unchanged or negligible increased (relative to the corresponding P,,,.of CGC).
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From the explanation of the algorithm, it can be concluded that it is not restricted to Manhattan environment, because the cell topology is “invisible” in the determination of the state of a cell. Indeed, when making a decision about accepting a new call request, the only relevant factor from the neighboring cells is the total number of users within them. Thus, the proposed call admission strategy could be applied to arbitrary cell topology. V. NUMERICAL RESULTS
We have compared three performance parameters: new call blocking probability P,, forced call termination probability PfiIand carried traffic T,. Fig. 3, 4 and 5 show Pnb, PfiI,T, as fictions of the offered traffic for CGC and the new strategy, for three different values of g (g=3,4,5), while the number of
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The figures show exactly what is expected: reduction of Pnb, increase of T, and negligible increase of PfiIwhen the new strategy is applied. This tendency is much more evident, as we increase the number of guard channels, what is explained by the fact that as g increases, a great percentage of new calls in CGC are rejected unfairly, while the new strategy “saves” a big part of them, without causing an significant increase in the number of the blocked handoff calls.
7-
Pnb, CGC, g=3
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channels allocated to each cell is N=14. The offered traffic is Tof=Up. The time interval T i s taken as T=(O.Sd)/v, where d is the cell length (d=lOO m), and v is the mean speed of the Pws is equal to the vehicle’s motion ( ~ 3 0k”). corresponding value of P,,,,when CGC is implemented.
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6
8
7
6
Offered Traffic(Eriangs)
(b) T, versus offered traffic TOR ;
(a) Pnb and PfiIversus offered traffic T&;
Fig.3. Comparison of CGC and new strategy for g=3.
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..+. .. Pnb, new strategy, g=4
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4 Offered Traffic (Eriangs)
6
8 Offered Traffic (Eriangs)
(a) Pnb and PfiIversus offered traffic T,;
(b) T, versus offered traffic TOf;
Fig.4. Comparison of CGC and new strategy for g=4.
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6
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Offered Traffic (Erlangs)
(a) P.6 and PfiIversus offered traffic TOT;
(b) T,versus offered traffic Tofl;
Fig.5. Comparison of CGC and new strategy for g=5.
VI. CONCLUDING REMARKS
[4] M. D. Kulavaratharasah and A. H. Aghvami, “Teletraffic performance evaluation of microcellular personal This paper describes a new algorithm for call admission control in a mobile cellular network. Since CGC gives good communication networks (PCN’s) with prioritized handoff performance as far as PfiIis concemed, but it deteriorates Pnb, procedures,” IEEE Trans. Veh. Technol., vol. 48 no.1 pp. the goal of the new policy is to reduce Pnb,while leaving Pfil 137-152, Jan. 1999 “A measurement-based unaffected. The new algorithm is an extension of CGC where [5] ’ S.Tekinay, B.Jabbari, decisions whether to reject a new call request or not, are prioritization scheme for handovers in mobile cellular based on past experience. The experimental results show that networks”, IEEE JSAC, October, 1992 our scheme improves the network performance. [6] R.Guerin, “Queueing-blocking system with two arrival streams and guard channels”, IEEE Transactions on It should be noted that the algorithm possesses significant level of generality, because it does not depend on the type of communications,February 1988 cellular structure, and it can adapt itself to any dynamic [7] R.Ramjee, R.Nagarajan, D.Towsley, “On optimal call fluctuations of a mobile traffic. admission control in cellular networks”, Wireless Networlrs Journal, January 1997 REFERENCES [8] N.D.Tripathi, J.H.Reed, H.F.VanLandingham, “Handoff in cellular systems”, IEEE Personal Communications, [11 D.Hong, S.S. Rappaport, “Traffic model and performance December 1998 analysis for cellular mobile radio telephone systems with prioritized and nonprioritized handoff procedures”, IEEE [9] T. Kwon, Y. Choi, “Call admission control in mobile cellular network based on macroscopic modeling of vehicular Trans. Vehic. Teh.,vol. VT-35, no.3, Aug.1986 traffic”, Dept. of Computer Engineering, Seoul National [2] A.Noerpel, Y.B. Lin, “Handover management for a PCS University, Seoul, Korea, 1998 network”, IEEE Personal Communications,December, 1997 [3] B. Jabbari, “Teletraffic aspects of evolving and next- [ 101 M. Au, R. Steele and M. Nofal, “Teletraffic performance generation wireless communication networks”, IEEE of different BS selection algorithms in street microcells”, Department of Electronics and Computer Science, University Personal Communications, pp. 4-9, Dec. 1996 of Southampton, 199516
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