SVD based sensing of a wireless microphone signal in cognitive radio networks

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