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.
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
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) [
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
can do is to provide some forms of probabilistic QoS guarantees by keeping HCDP below a predetermined value [
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.
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 [
Gelabert et al. in [
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 [
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 Hi (Hi H) denote the set of RATs which can support class-i calls in the heterogeneous cellular network, and let hi (hi h) denote the set of indices of all RATj which belong to Hi, where h = {1, 2, ···, J}. Furthermore, let Ji (Ji ≤ J) denote the total number of RATs that can support class-i calls. Let Dj (Dj 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 [
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
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
illustrated in
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, bi,w where bi,w belongs to the set Bi = {bi,w} for i = 1, 2,··· , K and w = 1, 2,··· , Wi. Wi is the number of different bandwidth values that a class-i call can be allocated. bi,1 (also denoted as bi,min) and bi,Wi (also denoted as bi,max) are, respectively, the minimum and maximum bandwidth that can be allocated to a class-i call. Note that bi,w < bi,(w+1) for i = 1, 2··· K and w = 1, 2··· (Wi − 1).
The requested bandwidth of class-i call is denoted by bi,req, where bi,req Bi. Let mi, j and ni, j denote, respectively, the number of new call of class-i and handoff call of class-i, in RATj. with 1 ≤ c ≤ mi,j (for new calls) and 1 ≤ c ≤ ni,j (for handoff calls). Let bi, assigned c denote the bandwidth assigned to call c of class-i in RAT-j in the group of co-located cells, where bi, assigned c Bi. A call c of class-i is degraded if bi, assigned c < bi,req whereas the call is upgraded if bi, assigned c > bi, 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 bi,min = bi,max and the set Bi 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 .
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.
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.