基于最大特征值的协作频谱检测算法

doi:1000-436X(2011)11A-0045-06

摘要/Abstract

摘要：

准确的频谱感知是实现认知技术的关键。根据随机矩阵理论，提出了一种认知网络中基于最大特征值的多节点协作频谱感知算法。该算法利用不同节点接收到主信号的相关性，将不同认知节点获取的采样信号构成接收信号矩阵，通过协方差矩阵的最大特征值构建频谱检测判决量，缩短了检测周期，提高了频谱检测性能。仿真结果表明，该协作算法与单节点MED算法相比改善了信噪比5dB左右。

关键词: 认知网络, 频谱感知, 协作检测, 随机矩阵理论, 特征值

Abstract:

Accurate spectrum sensing is the key to achieve cognitive techniques.According to analyzing random matrix,the cooperative spectrum sensing algorithm was proposed,which is based on the maximum eigenvalue.By use of the correlation of signals received at the different nodes,the maximum eigenvalue of the signals covariance matrix is used to decide whether the primary signal is present,which reduces the sensing period and improves the performance of spectrum sensing.Simulation results show that the cooperative algorithm has about 5dB margin better than the MED algorithm in signal-to-noise ratio.

Key words: cognitive network, spectrum sensing, cooperative detection, random matrix theory, eigenvalue

杨娇娇,张士兵,张昊晔. 基于最大特征值的协作频谱检测算法[J]. 通信学报, 2011, 32(11A): 45-50.

Jiao-jiao YANG,Shi-bing ZHANG,Hao-ye ZHANG. Cooperative spectrum sensing algorithm based on the maximum eigenvalue[J]. Journal on Communications, 2011, 32(11A): 45-50.

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t	F
?3.90	0.01
?2.78	0.10
…	…
0.45	0.90
0.98	0.95
2.02	0.99