Optimization for Average Throughput of Secondary Users in Cognitive Radio Networks

In cooperative spectrum sensing, previous numerical studies show that the sensing performance and the throughput of channel can be improved by increasing the secondary users which are participate in cooperative sensing. Due to the existence of channel capability, the throughput of channel can not be improved infinitely with the increasing number of secondary users, while the average throughput of secondary users decreases severely. In order to improve the average throughput of secondary users, the unimodal characteristics of the secondary users throughput are proved to be a function of the sensing time for any given fusion parameter in multi-channel environment. To solve this optimization issue, a cross iterative algorithm is proposed. Computer simulations show that when the average signal-to-noise ratio of secondary users is -10 dB, compared with the classical fusion rule, the proposed algorithm can gain more than 20% of the average throughput of secondary users.