基于模糊马尔可夫链预测的CR频谱接入算法

A Spectrum Access Algorithm based on Fuzzy Markov Chain Prediction in CR Networks

基于认知无线电(CR)的动态频谱接入技术,近年成为研究热点,但大部分算法都是根据当前授权用户的频谱活动情况来指导认知用户的频谱接入。本文研究了一种基于模糊马尔可夫链预测模型的动态频谱接入算法,该算法结合授权频段空闲时长的统计规律和模糊理论对信道状态进行预测,认知用户结合自身要求和信道状态的预测结果选择接入。仿真结果验证了该算法能有效提高认知系统的吞吐量和频谱利用率,改善通信质量。

The dynamic spectrum access（DSA） technology based on cognitive radio has recently become a research hotspot. However,most researchers put their focus on the current spectrum activity of primary users. This paper puts forward a dynamic spectrum access algorithm based on fuzzy Markov chain prediction model,which combine spectrum idle duration with statistical law and fuzzy theory. Cognitive users determine whether access the channel or not according to its own requirements and the prediction result. Simulation shows that the algorithm can effectively improves the throughput and the spectrum efficiency of cognitive system,further improves the communication quality of secondary users.