A PBNS Based Detection Algorithm for Cooperative Wideband Spectrum Sensing Using Hard Combining

Cooperative spectrum sensing (CSS) has been shown as an effective method to improve the detection performance by exploiting the spatial diversity. In this paper, we propose a detection algorithm for cooperative wideband spectrum sensing considering partial band Nyquist sampling (PBNS) in which all the cooperating secondary users (CSUs) posses antenna diversity with two receive antennas (diversity branches). We make use of hard combining at the fusion center (FC) since it requires reduced control channel bandwidth when compared to the soft combining. Novelty of our approach lies in use of hard combining to sense the wide band and making use of PBNS instead of sampling the entire wide band. Complete theoretical analysis of the proposed algorithm is carried out considering Nakagami fading channels. The proposed approach outperforms the ranked channel detection used under no cooperation and the performance is better than both ranked square law combining (R-SLC) and ranked square law selection (R-SLS) algorithms.