认知无线电网络中基于SVD算法的无线麦克风信号的检测

Sensing of wireless microphone signal in cognitive radio networks using singular value decomposition

在无线区域网中,作为授权用户的无线麦克风信号的低功率和窄带宽使得这种信号的检测非常困难。提出了基于奇异值分解的无线麦克风信号检测方法。对由接收信号形成的Hankel矩阵作奇异值分解,通过检查奇异值来检测无线麦克风信号的存在并估计该信号的中心频率,进而可以设置保护频带;非授权用户可以使用保护频带之外的频率资源,从而改善频谱效率。仿真结果证明了基于SVD的频谱检测算法具有更好的检测性能和很高的频率估计精度。

In a WRAN （wireless regional area network）, the presence of a WM （wireless microphone） signal must be detected as a primary user. However, very narrow bandwidth and low power makes it difficult to sense a WM signal. This paper presented an SVD （singular value decomposition） based approach to sense and estimate a WM signal. After performing SVD on the received data matrix, the presence of a WM signal could be detected and then the center frequency of a WM signal could be estimated. By doing so, retained a guard bandwidth such that the other spectrum in this sensing band was still available for the secondary users and the spectrum efficiency could be improved. Simulation results prove the better detection performance by comparing the proposed method with the traditional energy detection. Simulations also show a high frequency estimarion precision by using the proposed SVD based algorithm as well.