Spectrum Sensing in Cognitive Radio Using a Markov-Chain Monte-Carlo Scheme

被引：3

作者：

Wang, Xiao Yu ^{[1
]}

Wong, Alexander ^{[1
]}

Ho, Pin-Han ^{[1
]}

机构：

[1] Univ Waterloo, Waterloo, ON N2L 3G1, Canada

来源：

IEEE COMMUNICATIONS LETTERS | 2010年 / 14卷 / 09期

关键词：

Spectrum sensing; cognitive radio;

D O I：

10.1109/LCOMM.2010.080210.100569

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

In this letter, a novel stochastic strategy to spectrum sensing is investigated for the purpose of improving spectrum sensing efficiency of cognitive radio (CR) systems. The problem of selecting the optimal sequence of channels to finely sensing is formulated as an optimization problem to maximize the probability of obtaining available channels, and is then subsequently solved by using a Markov-Chain Monte-Carlo (MCMC) scheme. By employing a nonparametric approach such as the MCMC scheme, the reliance on specific traffic models is alleviated. Experimental results show that the proposed algorithm has the potential to achieve noticeably improved performance in terms of overhead and percentage of missed spectrum opportunities, thus making it well suited for use in CR networks.

引用

页码：830 / 832

页数：3

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