Paper Details

Cognitive radio (CR) is a new paradigm in wireless communication system which is use for efficientutilization of radio frequency (RF) spectrum or RF channel for future wireless communication. Cooperative spectrumsensing is a key technology in cognitive radio networks (CRNs) to detect spectrum holes by combining sensing result ofmultiple cognitive radio users. This sensing information from CR users combines at the Fusion center (common receiver)by soft combination or conventional hard combination techniques. Sensing error minimization is an important aspect ofcooperative spectrum sensing that needs attention. In this paper, the use of particle swarm optimization (PSO) underMINI-MAX criterion is proposed to optimize the weighting coefficients vector of energy level of spectrum sensinginformation so that the total probability of error is minimized. The particle swarm optimization (PSO) algorithminvestigates the best weighting coefficient vector which minimizes total probability of error. The performance of the PSObased method is analysed and compared with conventional soft decision fusion schemes like EGC as well as harddecision fusion method like AND,OR, Majority etc. Simulation results show that the proposed scheme minimizes thedetection error compared to conventional soft decision fusion schemes.

Prof. Keraliya Divyesh R, Dr. Ashalata Kulshrestha, “Minimizing the Detection Error in Cooperative Spectrum Sensing Using PSO”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 3, pp. 1743-1749, March 2018.