基于统计可信度的压缩感知协作频谱检测算法

压缩感知为认知无线电的宽频谱感知提供了一种新的方法和思路。基于压缩感知的原理，提出了一种多认知用户协作场景下基于用户统计可信度的协作频谱检测算法。该算法使用正交匹配协作追踪算法获得认知区域内的频谱占用情况，根据不同认知用户频谱检测的历史准确度综合判定用户感知结果的统计可信度。仿真结果表明，该算法在不同用户数、不同采样值、不同信噪比变化范围下其检测性能均优于传统算术平均方法，有效改善了检测性能。

Compressed sensing-based cooperative spectrum detection algorithm based on statistical dependability

Compressed sensing(CS) provides a new way for broad band spectrum sensing in cognitive radio(CR). According to the principle of compressed sensing,a cooperative spectrum detection algorithm based on user statistical dependability is proposed,which is used in the scenario of multiple cooperated cognitive users. The cooperative orthogonal matching-and-tracking algorithm is used in the proposed algorithm to obtain the spectrum occupation in the sensing area,and determines statistical dependability of different user according to their historical detecting accuracy. The simulation results show that the proposed algorithm has better performance than traditional algorithm in the conditions of different number of users,sample values and signal-to-noise ratio(SNR).