A Novel Binary Immune Elite Evolutionary Algorithm to Improve The Revenues of Spectrum Allocation In Medical Cognitive Radio Network

Medical cognitive radio network (MCRN) is a communication technology applied to cognitive electronic medical systems in recent years, and its spectrum is an important scarce resource. There is a phenomenon of low utilization between the rapidly growing demand for wireless spectrum resources and the existing spectrum allocation strategy. In view of the limited spectrum resources of MCRN, this paper proposes a novel binary immune elite evolutionary algorithm (BIEEA) to solve the problem of spectrum allocation. The algorithm uses binary encoding, and designs immune strategies and elite strategies to enhance the optimization capabilities of the algorithm. Under the same experimental conditions, BIEEA is compared with genetic algorithm (GA) and artificial bee colony (ABC) algorithm respectively. The simulation results show that the performance and convergence speed of the BIEEA are superior to the other two algorithms. In addition, BIQEA has high network revenue, which can improve the utilization of spectrum resources and effectively alleviate the shortage of spectrum resources, thereby improving the communication quality of the cognitive electronic medical system.