CASIA OpenIR  > 数字内容技术与服务研究中心  > 听觉模型与认知计算
Green Access Point Selection for Wireless Local Area Networks Enhanced by Cognitive Radio
Ge, Wendong1,2; Chen, Shanzhi3; Ji, Hong4; Li, Xi4; Leung, Victor C. M.5
Source PublicationMOBILE NETWORKS & APPLICATIONS
2013-08-01
Volume18Issue:4Pages:553-566
SubtypeArticle
AbstractIn wireless local area networks (WLANs) made up of Extended Service Sets, access point (AP) selection is a key issue to improve the network performance and balance the traffic load. WLANs operating in the shared Industrial, Scientific and Medical band can benefit from the use of cognitive radio (CR) techniques to enable dynamic access to spectrum holes that are free from interference. In this paper, we propose an optimal Green AP Selection (GAPS) scheme, in which AP selection is optimized to maximize the system throughput while minimizing the energy consumption, for multi-rate WLANs enhanced by CRs. Different from most existing AP selection schemes, GAPS takes into account of the state transition tendency of APs and the influence of Automatic Rate Fallback mechanism in the Distributed Coordination Function. The AP selection problem is formulated as a restless bandit problem and solved by the primal-dual index heuristic algorithm based on first order relaxation to yield the GAPS scheme with the "indexability" property and hence a low complexity. GAPS is further divided into offline computation, which accounts for the bulk of the computations, and online selection, with a low complexity to facilitate implementation. Extensive simulation results illustrate the significant performance improvements of GAPS compared with existing AP selection schemes in different scenarios.
KeywordWlans Cognitive Radio Access Point Selection Green Communication Restless Bandits
WOS HeadingsScience & Technology ; Technology
WOS KeywordDISTRIBUTED COORDINATION FUNCTION ; THROUGHPUT ANALYSIS ; CHANNEL ASSIGNMENT ; FADING CHANNELS ; 802.11 WLANS ; INTERFERENCE ; INDEX ; LAN
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Information Systems ; Telecommunications
WOS IDWOS:000321870400010
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3312
Collection数字内容技术与服务研究中心_听觉模型与认知计算
Affiliation1.Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.China Acad Telecommun Technol, State Key Lab Wireless Mobile Commun, Beijing 100027, Peoples R China
4.Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
5.Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V6T 1Z4, Canada
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Ge, Wendong,Chen, Shanzhi,Ji, Hong,et al. Green Access Point Selection for Wireless Local Area Networks Enhanced by Cognitive Radio[J]. MOBILE NETWORKS & APPLICATIONS,2013,18(4):553-566.
APA Ge, Wendong,Chen, Shanzhi,Ji, Hong,Li, Xi,&Leung, Victor C. M..(2013).Green Access Point Selection for Wireless Local Area Networks Enhanced by Cognitive Radio.MOBILE NETWORKS & APPLICATIONS,18(4),553-566.
MLA Ge, Wendong,et al."Green Access Point Selection for Wireless Local Area Networks Enhanced by Cognitive Radio".MOBILE NETWORKS & APPLICATIONS 18.4(2013):553-566.
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