Decentralized Utility Maximization in Heterogeneous Multicell Scenarios with Interference Limited and Orthogonal Air Interfaces

被引:14
作者
Blau, Ingmar [1 ]
Wunder, Gerhard [1 ]
Karla, Ingo [2 ]
Sigle, Rolf [2 ]
机构
[1] Heinrich Hertz Inst Nachrichtentech Berlin GmbH, Fraunhofer German Sino Lab Mobile Commu MCI, Fraunhofer Inst Telecommun, D-10587 Berlin, Germany
[2] Alcatel Lucent Deutschland AG, Bell Labs, D-70435 Stuttgart, Germany
来源
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING | 2009年
关键词
CONGESTION CONTROL; WIRELESS NETWORKS; POWER-CONTROL; ALLOCATION;
D O I
10.1155/2009/104548
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Overlapping coverage of multiple radio access technologies provides new multiple degrees of freedom for tuning the fairness-throughput tradeoff in heterogeneous communication systems through proper resource allocation. This paper treats the problem of resource allocation in terms of optimum air interface and cell selection in cellular multi-air interface scenarios. We find a close to optimum allocation for a given set of voice users with minimum QoS requirements and a set of best-effort users which guarantees service for the voice users and maximizes the sum utility of the best-effort users. Our model applies to arbitrary heterogeneous scenarios where the air interfaces belong to the class of interference limited systems like UMTS or to a class with orthogonal resource assignment such as TDMA-based GSM or WLAN. We present a convex formulation of the problem and by using structural properties thereof deduce two algorithms for static and dynamic scenarios, respectively. Both procedures rely on simple information exchange protocols and can be operated in a completely decentralized way. The performance of the dynamic algorithm is then evaluated for a heterogeneous UMTS/GSM scenario showing high-performance gains in comparison to standard load-balancing solutions. Copyright (C) 2009 Ingmar Blau et al.
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页数:12
相关论文
共 15 条
[1]  
[Anonymous], 1995, NONLINEAR PROGRAMMIN
[2]  
BLAU I, 2007, P 41 ANN C INF SCI S, P41
[3]  
BLAU I, 2007, P 18 IEEE INT S PERS, P1
[4]  
Borst Sem, 2006, PROC 4 INT S MODELIN, P1
[5]  
Boyd S., 2004, CONVEX OPTIMIZATION, DOI DOI 10.1017/CBO9780511804441
[6]   Balancing transport and physical layers in wireless multihop networks: Jointly optimal congestion control and power control [J].
Chiang, M .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2005, 23 (01) :104-116
[7]  
*ETSI, 2001, 101112V310 ETSI UMTS
[8]  
*ETSI, 1999, 101362V830 ETSI GSM
[9]   Multiservice allocation for multiaccess wireless systems [J].
Furuskär, A ;
Zander, J .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2005, 4 (01) :174-184
[10]  
Goldsmith, 2004, WIRELESS COMMUNICATI