Generalized FMD Detection for Spectrum Sensing Under Low Signal-to-Noise   Ratio
  Spectrum sensing is a fundamental problem in cognitive radio. We propose a function of covariance matrix based detection algorithm for spectrum sensing in cognitive radio network. Monotonically increasing property of function of matrix involving trace operation is utilized as the cornerstone for this algorithm. The advantage of proposed algorithm is it works under extremely low signal-to-noise ratio, like lower than -30 dB with limited sample data. Theoretical analysis of threshold setting for the algorithm is discussed. A performance comparison between the proposed algorithm and other state-of-the-art methods is provided, by the simulation on captured digital television (DTV) signal. 
Feng Lin, Robert C. Qiu, Zhen Hu, Shujie Hou, James P. Browning,   Michael C. Wicks
cs.AI