Dynamic RAT selection for multiple calls in heterogeneous wireless networks using group decision-making technique
Introduction
Joint radio resource management (JRRM) has been proposed for efficient radio resource utilization and enhanced QoS provisioning in heterogeneous wireless networks (HWNs), and a number of JRRM algorithms have been developed for HWNs [1], [2], [3]. The radio access technology (RAT) selection algorithm is one of the JRRM algorithms. The purpose of a RAT selection algorithm is to select the most suitable RAT for an incoming call in an HWN. Fig. 1 illustrates the problem of RAT selection for a single call in HWNs.
A number of RAT-selection algorithms have been proposed in the literature and these algorithms can be classified as single-criterion or multi-criteria RAT-selection algorithms. Single-criterion RAT selection algorithms use a single criterion for RAT selection whereas multi-criteria RAT selection algorithms use two or more criteria for RAT selection. Multi-criteria RAT-selection algorithms have been shown to be more efficient than single-criterion RAT selection algorithm. Thus much effort has been concentrated on developing multi-criteria RAT selection algorithms for HWNs [1], [3], [4], [5], [6], [7].
In [1], Giupponi and Pérez-Romero proposed a JRRM algorithm based on fuzzy neural approach for selecting the most appropriate RAT for an incoming call in HWNs.
In [3], Alkhawlani and Hussein proposed an intelligent RAT-selection algorithm for next generation wireless networks. The proposed algorithm uses a combined parallel fuzzy logic control and multi-criteria decision-making technique to select the most appropriate RAT for an incoming call in HWNs.
In [4], Zhang proposed a fuzzy multiple attribute decision-making (MADM) RAT-selection algorithm that uses fuzzy logic to represent imprecise information of some RAT-selection criteria. The fuzzy MADM method operates in two steps. The first step is to convert the imprecise fuzzy variables to crisp numbers. The second step is to use classical MADM technique to determine the ranking order of the candidate networks. The highest-ranking RAT is then selected for the call.
In [5], Xavier et al. presented a Markovian approach for RAT selection in an HWN. They developed an analytical model for a RAT-selection algorithm in an HWN comprising GSM/EGDE and UMTS. The proposed algorithm selects just one RAT for each incoming call.
In [6], Guo et al. proposed a RAT selection algorithm that uses a fuzzy multiple objective decision-making technique to select the most suitable RAT for each incoming call in an HWN.
In [7], Wu and Sandrasegaran conducted a study of RAT selection algorithm in a heterogeneous UMTS-GSM network.
All the RAT-selection algorithms reviewed above were designed to select the most suitable RAT for just one incoming call in HWNs. None of the RAT-selection algorithms considered the problem of RAT selection for a group of calls (multiple calls) from a multimode terminal (MT) in HWNs.
Multimode terminals (MTs) for next generation wireless networks have the capability to support two or more classes of calls simultaneously. Thus in a multi-service HWN, a subscriber using a multimode terminal (MT) will be able to access multiple services (such as voice, web session, video streaming, etc.) simultaneously, through any of the available RATs. Therefore, a group-call RAT selection problem occurs when a single RAT is to be selected for multiple classes of calls initiated from a multimode terminal in an HWN or when multiple classes of calls from a multimode terminal are to be handed over from one RAT to another.
Fig. 2 illustrates the problem considered in this paper, where a RAT is to be selected for multiple calls from an MT in an HWN.
As shown in Fig. 2, a user having an MT can initiate multiple calls from the MT, and a RAT has to be selected for the multiple calls in the HWN based on some RAT selection criteria. Different classes of calls have different QoS requirements, and different RATs in HWNs usually have different capabilities in terms of available data rate (bit per second), battery power consumption, security level provided, delay, etc. Selecting the most appropriate RAT for multiple calls from the MT in an HWN is a group decision problem. Existing RAT selection algorithms were not designed to select a RAT for multiple calls in HWNs.
Therefore, this paper addresses the problem of RAT selection for multiple calls from an MT using the modified TOPSIS group decision-making technique [8], [9].
The following are some reasons why it may be necessary to select a single RAT for multiple calls from a multimode terminal in HWNs: (1) to reduce handoff complexity, (2) to reduce signaling overhead, (3) to reduce battery power consumption, and (4) to accommodate low-capability multimode terminals.
If multiples calls from an MT are admitted into different RATs in an HWN, coordination of handover procedure among the different RATs will be complicated, and incur excessive signaling overhead. Moreover, multiple RAT interfaces of the multimode mobile terminals will be activated, which may increase the overall battery power consumption of the multimode terminal. In addition, some multimode terminals can be connected to only one RAT at a time. If these low-capability multimode terminals are to support multiple services, group decision is inevitable. Thus, it is necessary to develop an algorithm that will select the most suitable RAT for a group of calls from an MT in HWNs.
The objective of this paper is to develop a dynamic RAT-selection algorithm for making group call RAT-selection decisions in HWNs. The main contributions of this paper are threefold. The first is the conceptualization of group-call RAT-selection problem in HWNs. The second contribution is the development of a dynamic RAT selection algorithm and application of the modified TOPSIS group decision technique to solve the problem of RAT selection for multiple calls in HWNs. The third contribution is the investigation of the effect of RAT preference margin on the frequency of vertical handoff in HWNs. To the best of our knowledge, this is the first paper considering the problem of dynamic RAT selection for a group of calls from a multimode terminal in HWNs, and it is the first attempt to solve the problem.
The rest of this paper is organized as follows. In Section 2, multi-criteria group decision-making techniques are briefly reviewed. In Section 3, the proposed RAT selection algorithm is described. In Section 4, the modified TOPSIS group decision-making technique is applied to solve the problem of RAT selection for multiple calls in HWNs. Performance evaluation and simulation results are presented in Section 5.
Section snippets
Multi-criteria group decision-making techniques
In multi-criteria group decision-making (MCGDM) techniques, preference information on alternatives provided by decision-makers (experts) is aggregated to form a collective opinion. Then, ranking of the alternatives or selection of the best alternative is based on the derived collective opinions of the decision-makers [10]. The essence of group decision-making is to find the alternative among a set of feasible alternatives, which best reflects the preferences of the group of decision-makers as a
Description of the proposed RAT-selection procedure
We consider a dynamic RAT selection problem in which a RAT is to be selected for a call or multiple calls from an MT. The number of available RAT may not be fixed over time; it depends on the location of the MT in the HWN. The number of simultaneous calls from an MT is not fixed over time.
Application of the modified fuzzy TOPSIS group decision-making technique for RAT selection in HWNs
In this section, we apply the modified fuzzy TOPSIS procedure [8] to solve the problem of RAT selection for a single or multiple calls from a multimode terminal in HWNs. The basic function of the proposed RAT selection algorithm is to select the most suitable RAT for a single or multiple calls from an MT in HWNs.
Performance evaluation and results
In this section, we evaluate the performance of the proposed RAT-selection algorithm through numerical simulations conducted in MATLAB. We use three-service three-RAT network as an example of HWN supporting multimode terminals. Only vertical handoffs due to call-events are considered in the simulations. To study the performance of proposed algorithm based on call events, it is assumed that the three RATs are available for all the calls considered in the simulations. A RAT is available when it
Conclusion
Next generation multimode terminals have the capability to simultaneously support two or more different classes of calls in HWNs. Existing RAT selection algorithms do not consider the problem of RAT selection for multiple calls in HWNs. In this paper, the problem of RAT selection for multiple calls in HWNs has been conceptualized. A RAT selection algorithm has been proposed and the fuzzy TOPSIS group decision-making technique has been applied to solve the problem of RAT selection for single and
Olabisi E. Falowo received his PhD in Electrical Engineering at the University of Cape Town in 2008. He has published over 25 papers in reputable conferences and journals including Computer Communications, EURASIP Journal on Wireless Communications and Networking, Telecommunications Systems, International Journal of Communications, and Wireless Communications and Mobile Computing. He is currently a senior lecturer in the Department of Electrical Engineering, University of Cape Town. His primary
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Olabisi E. Falowo received his PhD in Electrical Engineering at the University of Cape Town in 2008. He has published over 25 papers in reputable conferences and journals including Computer Communications, EURASIP Journal on Wireless Communications and Networking, Telecommunications Systems, International Journal of Communications, and Wireless Communications and Mobile Computing. He is currently a senior lecturer in the Department of Electrical Engineering, University of Cape Town. His primary research interest is in radio resource management in heterogeneous wireless networks. Olabisi is member of the IEEE and the IET.
H. Anthony Chan (M’94–SM’95–F’08) received his PhD in physics at University of Maryland, College Park in 1982 and then continued post-doctorate research there in basic science. After joining the former AT&T Bell Labs in 1986, his work moved to industry-oriented research in areas of interconnection, electronic packaging, reliability, and assembly in manufacturing, and then moved again to network management, network architecture and standards for both wireless and wireline networks. He had designed the Wireless section of the year 2000 state-of-the-art Network Operation Center in AT&T. He was the AT&T delegate in several standards work groups under 3rd generation partnership program (3GPP). During 2001–2003, he was visiting Endowed Pinson Chair Professor in Networking at San Jose State University. In 2004, he joined University of Cape Town as professor in the Department of Electrical Engineering.
He was Administrative Vice President of IEEE CPMT Society and had chaired or served numerous technical committees and conferences. He is distinguished speaker of IEEE CPMT Society and is in the speaker list of IEEE Reliability Society since 1997.