NDLI: Delay analysis and optimal access strategy in multichannel dynamic spectrum access system

Content Provider	IEEE Xplore Digital Library
Author	Xiao Li Jun Wang Husheng Li Shaoqian Li
Copyright Year	2012
Description	Author affiliation: The Department of Electrical Engineering and Computer Science, the University of Tennessee, Knoxville, TN, USA (Husheng Li) \|\| National Key Lab of Science and Technology on Communications, University of Electronic Science and Technology, Chengdu, P.R. China (Xiao Li; Jun Wang; Shaoqian Li)
Abstract	In this paper, we consider a hierarchical cognitive radio scenario where the secondary users (SUs) may access the licensed spectrum opportunistically, whenever it is not occupied by the primary users (PUs). Our work focuses on the delay performance analysis of the SU system and the optimal access strategy for the case of sharing multiple licensed channels among SUs. By merging the PU traffic with SU traffic, we propose the model of priority virtual queue on licensed channels. Based on this model, we obtain the expected system delay expression of SU traffic through M/G/1 preemptive repeat priority queuing analysis. For the case of multiple licensed channel access, the access strategy is further investigated to minimize the expected transmission delay of SU traffic. The optimal access strategy is modeled as a nonlinear programming problem, which can be resolved by means of classic Genetic Algorithm (GA). Numerical results validate our analysis and optimal access strategy design.
Starting Page	376
Ending Page	380
File Size	171613
Page Count	5
File Format	PDF
ISBN	9781467300087
e-ISBN	9781467300094
e-ISBN	9781467307239
DOI	10.1109/ICCNC.2012.6167447
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-01-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Programming Cognitive radio Delay Queueing analysis Optimization Equations Genetic algorithms
Content Type	Text
Resource Type	Article

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