基于卡方检验的多天线认知无线网络协作频谱感知算法

Cooperative spectrum sensing using Chi-square test for multi-antenna cognitive radio

研究了基于分集的多天线认知无线网络的频谱感知技术。针对天线独立性会导致已有的基于协方差矩阵的协作频谱感知算法性能急剧下降甚至失效的问题,提出了一种基于卡方拟合优度检验的多天线协作频谱感知算法。该算法将频谱感知问题转化为一个多项分布检验的问题,然后利用卡方拟合优度检验判决频谱是否空闲,从而实现频谱感知。理论分析和仿真表明,该算法的性能不受天线相关性以及噪声不确定度的影响。

The spectrum sensing of diversity-based multiple antenna cognitive radio systems was studied. To solve the problem that the performance of the existing cooperative spectrum sensing algorithm based on covariance matrix degrades seriously due to the channel independence, a new cooperative spectrum sensing algorithm based on Chi-square goodness of fit test for multi-antenna cognitive radio systems was presented. The algorithm transforms the spectrum sensing problem into a muhinomial distribution test problem, and uses the Chi-square goodness of fit test to examine a spectrum if idle so as to realize spectrum sensing. The theoretical analysis and simulation show that the performance of the proposed algorithm is robust to the antenna correlation and noise uncertainty.