Optimization of spectrum allocation for symbiotic and time-variable binary salp swarm algorithm

For the difficult problems of spectrum allocation optimization and optimal convergence accuracy in cognitive radio networks, a symbiotic time-varying binary salp swarm algorithm is proposed to basis of graph theory model and applied to the optimization of cognitive radio spectrum allocation. Firstly, a symbiotic strategy is introduced in the follower location to enhance development capabilities. Secondly, the time-variable function is introduced to disperse the position in the process of continuous space and discrete space conversion. Finally, the improved binary salp swarm algorithm and the other algorithm are compared with the goal of maximizing total system benefit and fairness of secondary user. The results show that the improved binary salp swarm algorithm is superior to other algorithms in the application and can be effectively and stably used for spectrum allocation optimization.