Competitive spectrum allocation in cognitive radio based on idle probability of primary users

Shuai Liu, Yutao Liu, Xuezhi Tan
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引用次数: 2

Abstract

Cognitive radio is recognized as an efficient way to improve the spectrum efficiency. In the distributed cognitive radio networks of multiple primary users and a secondary user, we proposed a utility function based on idle probability of primary users by using game model. The primary users can achieve the Nash equilibrium by adjusting the learning rate through repeated games. Simulations show that the primary user whose idle probability is larger, the system utility is higher and the system utility becomes the largest when the spectrum offered by primary users is totally idle. Besides, the Nash equilibrium is not efficient as the total profit of the primary users is not maximized. The cooperative optimality solution can obtain the highest system profit finally.
基于主用户空闲概率的认知无线电频谱竞争分配
认知无线电被认为是提高频谱利用率的有效途径。在由多个主用户和一个副用户组成的分布式认知无线网络中,利用博弈模型提出了基于主用户空闲概率的效用函数。初级用户通过重复博弈调整学习速率,达到纳什均衡。仿真结果表明,当主用户提供的频谱完全空闲时,主用户的空闲概率越大,系统效用越高,系统效用最大。此外,由于主要用户的总利润没有最大化,纳什均衡不是有效的。合作最优解最终能获得最大的系统利润。
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