Dynamic RAT selection for multiple calls in heterogeneous wireless networks using group decision-making technique

被引:27
作者
Falowo, Olabisi E. [1 ]
Chan, H. Anthony [1 ]
机构
[1] Univ Cape Town, Dept Elect Engn, ZA-7700 Rondebosch, South Africa
关键词
Dynamic RAT selection; Group decision-making; Multiple calls; Heterogeneous wireless network; TOPSIS method; Radio resource management; TOPSIS;
D O I
10.1016/j.comnet.2011.12.013
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
Existing radio access technology (RAT)-selection algorithms for heterogeneous wireless networks (HWNs) do not consider the problem of RAT selection for a group of calls from a multimode terminal (MT). Multimode terminals (MTs) for next generation wireless networks have the capability to support two or more classes of calls simultaneously. When a new call is initiated on an MT already having an ongoing call in an HWN, the current RAT may no longer be suitable for the two calls (incoming call and the existing call). Thus, a new RAT may be more suitable for the two calls. The problem of RAT selection for two or more calls from an MT in an HWN is a group decision problem. This paper addresses the problem of RAT selection for a group of calls from an MT in an HWN by using the modified TOPSIS group decision-making technique. The paper proposes a dynamic RAT-selection algorithm that selects the most suitable RAT for a single call or group of calls from an MT in an HWN. The algorithm considers users' preferences for individual RATs, which vary with each class of calls, in making RAT selection decisions in an HWN. A user's preference for each of the available RATs is specified by weights assigned by the user to RAT selection criteria for different classes of calls. Based on the assigned weights, the proposed algorithm aggregates individual calls' weights specified by the user to make a RAT-selection decision for a group of calls. In order to reduce the frequency of vertical handover, the proposed algorithm uses RAT preference margin in making RAT selection decisions. RAT preference margin is a measure of the degree to which the newly preferred RAT is better than the current RAT. Performance of the proposed algorithm is evaluated through numerical simulations. Results are given to show the effectiveness of the proposed RAT-selection algorithm. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:1390 / 1401
页数:12
相关论文
共 20 条
[1]
Alkhawlani M. M., 2010, P 7 INT C INF SYST I
[2]
[Anonymous], 1992, Fuzzy Multiple Attribute Decision Making: Methods and Applications
[3]
Bernardes P., 2008, PROGR NONLINEAR ANAL, P247
[4]
A linguistic modeling of consensus in group decision making based on OWA operators [J].
Bordogna, G ;
Fedrizzi, M ;
Pasi, G .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 1997, 27 (01) :126-132
[5]
Fuzzy set based models and methods of multicriteria group decision making [J].
Ekel, P. ;
Queiroz, J. ;
Parreiras, R. ;
Palhares, R. .
NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS, 2009, 71 (12) :E409-E419
[6]
Falowo O.E., 2007, ELSEVIER J COMPUTER, V31, P1200, DOI DOI 10.1016/J.COMCOM.2007.10.044
[7]
An Approach to Solve Group-Decision-Making Problems With Ordinal Interval Numbers [J].
Fan, Zhi-Ping ;
Liu, Yang .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2010, 40 (05) :1413-1423
[8]
A Markovian approach to Radio Access Technology selection in heterogeneous multiaccess/multiservice wireless networks [J].
Gelabert, Xavier ;
Perez-Romero, Jordi ;
Sallent, Oriol ;
Agusti, Ramon .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2008, 7 (10) :1257-1270
[9]
A novel approach for joint radio resource management based on fuzzy neural methodology [J].
Giupponi, Lorenza ;
Agusti, Ramon ;
Perez-Romero, Jordi ;
Roig, Oriol Salient .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2008, 57 (03) :1789-1805
[10]
A QoS-guaranteed cell selection strategy for heterogeneous cellular systems [J].
Guo, Q ;
Xu, XH ;
Zhu, J ;
Zhang, HB .
ETRI JOURNAL, 2006, 28 (01) :77-83