Adaptive Terminal-Modality-Based Joint Call Admission Control for Heterogeneous Cellular Networks

Mahmoud M. Badawy, Salman A. AlQahtani

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Computer Engineering Department, King Saud University, Riyadh, Saudi Arabia.

DOI: 10.4236/ijcns.2013.69043                

Abstract

The coexistence of different Radio Access Technologies (RATs) requires a need for Common Radio Resource Management (CRRM) to support the provision of Quality of Service (QoS) and the efficient utilization of radio resources. The provision of QoS is an important and challenging issue in the design of integrated services packet networks. Call admission control (CAC) is an integral part of the problem. Clearly, without CAC, providing QoS guarantees will be impossible. There is unfairness in allocation of radio resources among heterogeneous mobile terminals in heterogeneous wireless networks. In this paper, an Adaptive-Terminal Modality-Based Joint Call Admission Control (ATJCAC) algorithm is proposed to enhance connection-level QoS and reduce call blocking/dropping probability. The proposed ATJCAC algorithm makes call admission decisions based on mobile terminal modality (capability), network load, adaptive the bandwidth of ongoing call and radio access technology (RAT) terminal support index. Simulation results show that the proposed ATJCAC scheme reduces call blocking/dropping probability.

Keywords

Call Admission Control; Call Blocking; Call Dropping; Next Generation Wireless Network (NGWN); RAT Selection Approaches

1. Introduction

Network heterogeneity refers to a combination of multiple wireless networks based on different access technologies (e.g. UMTS, EV-DO, LTE, WiMAX, etc.) coexisting in the same geographical area. Due to the coexistence of different Radio Access Technologies (RATs), Next Generation Wireless Networks (NGWN) are predicted to be heterogeneous in nature. The coexistence of different RATs requires a need for Common Radio Resource Management (CRRM) to support the provision of Quality of Service (QoS) and the efficient utilization of radio resources. With joint radio resource management in NGWN, mobile users will be able to communicate through any of the available radio access technologies (RATs) and roam from one RAT to another, using multimode terminals (MTs) as shown in Figure 1 [1-3].

Next generation wireless cellular networks, including 3G and 4G technologies are envisaged to support more mobile users and variety of high-speed Wireless Multimedia Services (WMSs). A WMS enables the simultaneous transmission of voice, data, text and images through radio links by means of the new wireless technologies. Different WMSs have diverse bandwidth and Quality of Service (QoS) requirements from their users that need to be guaranteed by wireless cellular networks. In wireless cellular networks, user’s QoS requirements can be quantitatively expressed in terms of probabilistic connection-level QoS parameters such as new call blocking probability (NCBP) and handoff call dropping probability (HCDP) [4]. The NCBP is the probability of a new arriving call being rejected while the HCDP is the probability that an accepted call is terminated before the completion of its service, i.e., the probability that a handoff attempt fails [4].

Provisioning connection-level QoS in wireless cellular networks becomes complex due to 1) The limited radio link bandwidth, and 2) The high rate of handoff events as the next generation of wireless cellular networks will use micro/pico cellular architectures in order to provide higher capacity. Therefore, one of the most important connection-level QoS issues is how to reduce/control handoff drops due to lack of available resources in the new cell, since mobile users should be able to continue their ongoing connections. Since it is practically impossible to completely eliminate handoff drops, the best one

Figure 1. The coexistence of different RATs.

can do is to provide some forms of probabilistic QoS guarantees by keeping HCDP below a predetermined value [5].

In the 3G and beyond wireless systems, multimedia services such as voice, video, data, and audio are to be offered with various quality-of-service (QoS) profiles. Hence, more sophisticated call admission control (CAC) schemes are developed to cope with these changes. Traffic of admitted calls is then controlled by other RRM techniques such as scheduling, handoff, power, and rate control schemes. 

RAT selection algorithms are part of the CRRM algorithms. Simply, their role is to verify if an incoming call will be suitable to fit into a heterogeneous wireless network, and to decide which of the available RATs is most suitable to fit the need of the incoming call and admit it. Guaranteeing the requirements of QoS for all accepted calls and at the same time being able to provide the most efficient utilization of the available radio resources is the goal of RAT selection algorithm. Call admission control is a key element in the provision of guaranteed quality of service in wireless networks. The design of call admission control algorithms for mobile cellular networks is especially challenging given the limited and highly variable resources, and the mobility of users encountered in such networks.

Generally, CAC algorithms are triggered by any of the following events: New call arrival and handoff call arrival. The normal call admission control algorithms do not provide a solution to fit a heterogeneous wireless network. Therefore, there is a need to develop RAT selection algorithm in addition to Call admission control. This guarantees a term called Joint call admission control (JCAC) algorithm.

In this paper, an Adaptive-Terminal Modality-Based Joint Call Admission Control (ATJCAC) algorithm is proposed to enhance connection-level QoS and reduce call blocking/dropping probability. The ATJCAC scheme is designed to simultaneously achieve the following objectives in heterogeneous cellular networks:

1) Ensure fairness in allocation of radio resources among heterogeneous mobile terminals;

2) Adapt the bandwidth of ongoing calls to improve connection-level QoS;

3) Guarantee the QoS requirement of all admitted calls;

4) Prioritize handoff calls over new calls.

The rest of this paper is organized as follows. The related work is presented in the next section. In Section 3, the system model is described. The proposed adaptiveTJCAC scheme is presented in Section 4. In Section 5, result discussions of the proposed scheme are provided. Finally, the conclusion of this research is presented in Section 6.

2. Literature Review

A number of RAT selection algorithms including initial RAT selection and vertical handover have been proposed in the literature for heterogeneous wireless networks [1,2, 6-14]. Reference [14] presents a good revision on these algorithms. Each one has its benefits and limitations. O. E. Falowo et al. in paper [1] review the recent call admission control algorithms for heterogeneous wireless networks. The benefits and requirements of JCAC algorithms are discussed. The authors examine eight different approaches for selecting the most appropriate RAT for incoming calls in HWN and classify the JCAC algorithms based on these approaches. The advantages and disadvantages of each approach are discussed. The same authors in [2] propose a JCAC algorithm which considers the users preference in making an admission decision and a specific case where the user prefers to be served by the RAT which has the least service cost is modeled and evaluated. In [6] a JCAC scheme for multimedia traffic that maximizes the overall network revenue with QoS constraints over coupled WLAN and CDMA cellular network is considered. X. G. Wang et al. in [7] proposed an adaptive call admission control for integrated cellular and WLAN network. In this proposed scheme, call admission decisions are based on requested QoS and availability of radio resources in the considered RATs. D. Karabudak et al. in [8] proposed a call admission control scheme for the heterogeneous network using genetic algorithm. The objectives of the scheme are to achieve maximum wireless network utilization and meet QoS requirements. A network capacity policy based joint admission controller is presented by K. Murray et al. in [9,10]. D. Qiang et al. in [11] proposed a joint admission control scheme for multimedia traffic that exploits vertical handoffs as an effective tool to enhance radio resource management while guaranteeing handoff users QoS requirements. The network resources utilized by the vertical handoff user are captured by a link utility function. X. Li et al. in [12] proposed an efficient joint session admission control scheme that maximizes overall network revenue with QoS constraints over both the WLAN and the TD-SCDMA cellular networks. In [13], the authors proposed a call admission control reservation algorithm that takes resource fluctuations into consideration. They considered two types of applications denoted by wide-band and narrow band. The performance of the algorithm was modeled through a queuing theory approach and its main performance measures are compared with a conventional algorithm through simulation. The authors in [14] proposed an algorithm, which incorporates traditional Admission Control (AC) and Wiener Process (WP)-based prediction algorithms to determine when to carry out access service network gateway relocation.

Gelabert et al. in [15] presented a Markovian approach to RAT selection in heterogeneous wireless networks. They developed an analytical model for RAT selection algorithms in a heterogeneous wireless network comprising GSM/EGDE and UMTS. The proposed algorithm selects just one RAT for each call. In [16], a service-class based JCAC algorithm was proposed. it admits calls into a particular RAT based on the class of service, such as voice, video streaming, real-time video, web browsing, etc. in [17], a terminal-modality-based JCAC scheme was proposed. It consists of two main components: joint call admission controller and band-width reservation unit.

3. System Model and Assumptions

We consider a heterogeneous cellular network which consists of J number of RATs with co-located cells. A typical example of a heterogeneous wireless network, adapted from [16] is shown in Figure 2. In the heterogeneous network, radio resources are jointly managed. Cellular networks such as GSM, UMTS (3G) and LTE can have the same and fully overlapped coverage, which is technically feasible, and may also save on installation costs [18,19]. Let H denote the set of all available RATs in the heterogeneous wireless network.

Then, H is given as follows:

where J is the total number of RATs in the heterogeneous cellular network. The heterogeneous cellular network supports k-classes of calls, and each RAT in set H is optimized to support certain classes of calls. Let H_i (H_i H) denote the set of RATs which can support class-i calls in the heterogeneous cellular network, and let h_i (h_i h) denote the set of indices of all RATj which belong to H_i, where h = {1, 2, ···, J}. Furthermore, let J_i (J_i ≤ J) denote the total number of RATs that can support class-i calls. Let D_j (D_j D) denotes the set of call classes that can be supported by RATj (j = 1, 2, ···, J) where D = {class-1, class-2, ···, class-k}. Note that the idea that different networks support different classes of calls is true in reality. For example, LTE and UMTS network can support video streaming whereas GSM network cannot support video streaming.

Each cell in RATj (j = 1, ···, J) has a total of Bj basic bandwidth units (bbu). The physical meaning of a unit of radio resources (such as time slots, code sequence, etc.) is dependent on the specific technological implementation of the radio interface [20]. However, no matter which multiple access technology (FDMA, TDMA, WCDMA or OFDMA) is used, system capacity could be interpreted in terms of effective or equivalent bandwidth [21-22]. Therefore, this research refers to the bandwidth of a call as the number of bbu that is adequate for guaranteeing the desired QoS for the call, which is similar to the approach used for homogeneous networks in [22,23].

It is assumed that packet-level QoS is stochastically assured by allocating at least the minimum effective bandwidth required to guarantee a given maximum probability on packet drop, delay, and jitter. The approach used is to decompose a heterogeneous cellular network into groups of co-located cells as shown in Figure 3.

For example, cell 1a and cell 2a form a group of colocated cells. Similarly, cell 1b and cell 2b form another group of co-located cells, and so on. When a mobile user with an ongoing call is moving outside the coverage area of a group of co-located cells, the call must be handed over to one of the cells that can support the call in the neighboring group of co-located cells. For example, in the two-class three-RAT heterogeneous cellular network

Figure 2. A typical two-RAT heterogeneous cellular network with co-located.

Figure 3. Two-RAT heterogeneous cellular networks with co-located cells.

illustrated in Figure 3, an ongoing class-1 call can be handed over from cell 2a to cell 2b, or from cell 2a to cell 1b. Note that hand-off comprises both horizontal and vertical handoffs.

The correlation between the groups of co-located cells results from handoff connections between the cells of corresponding groups. Under this formulation, each group of co-located cells can be modeled and analyzed individually. Therefore, a single group of co-located cells is considered in this research. The heterogeneous network supports K classes of calls. Each class is characterized by bandwidth requirement, arrival distribution, and channel holding time. Each class-i call requires a discrete bandwidth value, b_i,w where b_i,w belongs to the set B_i = {b_i,w} for i = 1, 2,··· , K and w = 1, 2,··· , W_i. W_i is the number of different bandwidth values that a class-i call can be allocated. b_i,1 (also denoted as b_i,min) and b_i,Wi (also denoted as b_i,max) are, respectively, the minimum and maximum bandwidth that can be allocated to a class-i call. Note that b_i,w < b_i,(w+1) for i = 1, 2··· K and w = 1, 2··· (W_i − 1).

The requested bandwidth of class-i call is denoted by b_i,req, where b_i,req B_i. Let m_{i, j} and n_{i, j} denote, respectively, the number of new call of class-i and handoff call of class-i, in RATj. with 1 ≤ c ≤ m_i,j (for new calls) and 1 ≤ c ≤ n_i,j (for handoff calls). Let b_{i, assigned c} denote the bandwidth assigned to call c of class-i in RAT-j in the group of co-located cells, where b_{i, assigned c} B_i. A call c of class-i is degraded if b_{i, assigned c} < b_i,req whereas the call is upgraded if b_{i, assigned c} > b_{i, req}. If a class of calls (i.e., class-i calls) requires a fixed number of bbu (i.e. constant bit-rate service), it becomes a special case in our model in which b_i,min = b_i,max and the set B_i has only one element. However, it will not be possible to upgrade or degrade this class of calls.

We define the following terms commonly used in the literature to be used throughout this paper.

1) Call holding time: It is duration of the requested call connection. This is a random variable which depends on the user behavior (call characteristics).

2) Cell residency time: It is amount of time during which a mobile terminal stays in a cell during a single visit. Cell residency is a random variable which depends on the user behavior and system parameters, e.g. cell geometry.

3) Channel holding time: How long a call which is accepted in a cell and is assigned a channel will use this channel before completion or handoff to another cell? This is a random variable which can be computed from the call holding time and cell residency time and generally is different for new calls and handoff calls.

Following are the general assumptions in the studied cellular networks. The New call arrival of class-i arrive is assumed to follow Poisson process with rate , n denoted to new call. Handoff call of class-i arrive according to Poisson process with rate , h denoted to handoff call. Call holding time (CHT) of class-i is assumed to exponential distribution with mean . Cell residence time (CRT) is assumed to follow an exponential distribution with mean , h denoted to handoff rate. Channel holding time for call of class-i is assumed to exponential distribution with mean where .

4. Proposed Adaptive TJCAC Scheme

This section describes the proposed adaptive terminalmodality-based JCAC scheme. In fact, the joint call admission control (JCAC) algorithm is one of the RRM algorithms. The basic function of JCAC algorithms is to decide whether an incoming call can be accepted or not. They also decide which of the available radio access technology is most suitable to accommodate the incoming call. Figure 4 shows call admission control procedure in heterogeneous cellular networks.

When these mobile terminals make a call, then they will send a service request to the JCAC algorithm. The JCAC scheme, which executes the JCAC algorithm, will then select the most suitable RAT for the incoming call.

Figure 5 illustrates the problem of unfairness in radio resource allocation in a three-RAT heterogeneous wireless network when terminal modality is not considered in making RAT selection decisions. Assume that 1) all the three RATs have equal capacity; 2) all the arriving calls belong to the same class; and 3) each RAT can support only two calls. Figure 5 shows six consecutively arriving calls (1 to 6) in the heterogeneous wireless network. A load-balancing JCAC scheme, for instance, will admit the

Conflicts of Interest

The authors declare no conflicts of interest.

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