Optimal channel selection strategy based on maximizing throughput in Cognitive Radio Network

Aiming at the problem of different idle probability and the gain of each channel in the cognitive radio network, in order to enable cognitive user to transmit successfully, the successful completion probability of cognitive users is introduced, and an optimal channel selection strategy based on maximizing system throughput is proposed. This strategy comprehensively considers the channel gain, channel idle probability, and access channel probability of cognitive users to obtain the channel selection optimization model. Considering that the system throughput reflected by the objective function in this model only depends on the access channel probability of cognitive users, a genetic algorithm is designed to solve this optimization problem by controlling the probability. Simulation experiments are conducted to analyze the performance of the proposed strategy in terms of system throughput, transmission delay and communication outage probability. It is shown that the proposed strategy has better throughput and can significantly reduce the transmission delay and outage probability of cognitive users.