Analysis of Hard-Decision and Soft-Data Fusion Schemes for Cooperative Spectrum Sensing in Rayleigh Fading Channel

This paper investigates the performance of hard-decision and soft-data fusion schemes for a cooperative spectrum sensing (CSS) in noisy-Rayleigh faded channel. Hard-decision fusion operations on the local binary decisions and soft-data fusion operations on the energy values obtained from the different cognitive radio (CR) users are performed at fusion center (FC) and a final decision on the status of a primary user (PU) is made. More precisely, the performance of CSS with various hard-decision fusion schemes (OR-rule, AND-rule, and majority-rule) and soft-data fusion schemes (square law selection (SLS), maximal ratio combining (MRC), square law combining (SLC), and selection combining (SC)) is analyzed in this work. Towards that, novel and closed-form analytic expressions are derived for probability of detection under all soft schemes in Rayleigh fading channel. A comparative performance between hard-decision and soft-data fusion schemes has been illustrated for different network parameters: time-band width product, average sensing channel signal-to-noise ratio (SNR), and detection threshold. The optimal detection thresholds for which minimum total error rate is obtained for both soft and hard schemes are also indicated.