Dynamic spectrum access with learning for cognitive radio

被引：5

作者：

Unnikrishnan, Jayakrishnan ^{[1
,2
]}

Veeravalli, Venugopal V. ^{[1
,2
]}

机构：

[1] Univ Illinois, Dept Elect & Comp Engn, Urbana, IL USA

[2] Univ Illinois, Coordinated Sci Lab, Urbana, IL USA

来源：

2008 42ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-4 | 2008年

关键词：

D O I：

10.1109/ACSSC.2008.5074371

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We study the problem of cooperative dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). Assuming Markovian state-evolutions for the primary channels, we propose a greedy channel selection and access policy that satisfies an interference constraint and also outperforms some existing schemes in average throughput. When the distribution of the signal from the primary is unknown and belongs to a parameterized family, we develop an algorithm that can learn the parameter of the distribution still guaranteeing the interference constraint. This algorithm also outperforms the popular approach that assumes a worst-case value for the parameter thus illustrating the sub-optimality of the popular worst-case approach.

引用

页码：103 / +

页数：2

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