Semi-Blind Locally Optimum Detection for Spectrum Sensing in Cognitive Radio
Source: University of Leeds
Spectrum sensing in cognitive radio becomes a challenging task when the signals received at the secondary users' transmitters exhibit low power. Locally Optimum Detectors (LOD) are therefore desirable, thanks to their optimality in the low SNR regime. Here, the authors assume that the primary user transmits a training sequence, and propose a Semi-Blind LOD (SBLOD). In the case of BPSK signals, the test statistic of the proposed SBLOD is shown to be a weighted sum of the matched filter output, the energy and pseudo-energy. For higher size constellations, the SBLOD reduces to a linear combination of the matched filter and the energy detector.