Spectrum Detection Performance of HSTLBO Based Energy Sensing Algorithm in Cognitive Radio Networks

摘要

Spectrum detection plays a critical role in the performance of cognitive radio networks. In this work, spectrum detection performance in cognitive radio networks is investigated by using harmony search and teaching-learning-based optimization (HSTLBO) algorithm. First, the threshold level is optimized with energy detection to minimize spectrum detection error. Then, spectrum detection performance of HSTLBO algorithm is obtained by computer simulations on the AWGN channel and Rayleigh fading channel.