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.
