Cognitive radio (CR) is a new paradigm in the field of wireless communication system for efficient utilization of radio frequency (RF) spectrum. The cooperative spectrum sensing is the key component of cognitive radio technology in which the sensing information from CR users combines at the fusion centre (common receiver) by soft combination or conventional hard combination techniques. Soft combination has excellent performance but, it requires a lot of overhead. In contrast, the conventional hard combination scheme requires only one bit of overhead, but it has worst performance because of the loss of sensing information. In this paper, the use of teaching learning based optimization (TLBO) algorithm based on the Neyman-Pearson criterion as a significant method is proposed to optimize the weighting coefficients vector of observed energy level of sensing information so that the probability of detection is improved. The proposed technique investigates the best weighting coefficients vector and compared the performance of the TLBO based proposed method with soft combination technique EGC as well as other conventional hard combination scheme like AND, OR, MAJORITY etc. through computer simulations. Simulation result shows that proposed TLBO based method gives excellent detection performance with low overhead.

cognitive radio, cooperative spectrum sensing, hard combination, soft combination, TLBO.