基于离散粒子群优化算法的合作感知调度方案

摘要

采用CTMC模型分析了网络状态的统计特性,考虑各个次用户感知能力的差异性,分别从主用户和次用户的角度出发,建立了2个关于次用户调度方案的整数规划问题.提出了通过离散粒子群优化算法求解所建问题,并与传统的随机调度方案和基于信噪比的贪婪调度方案进行了比较.仿真结果表明,所提调度方案获得的感知性能更高.%The statistical characteristics of the network state changes were analyzed by using the CTMC model. Consi-dering the difference of each secondary user's sensing ability, two integer programming problems on cooperative sensing scheduling scheme were established from two aspects: the primary users and the secondary users respectively. A discrete particle swarm optimization algorithm was proposed to solve the integer programming problems, and compared with the traditional random scheduling scheme and greedy scheduling scheme based on SNR. The simulation results show that the cooperative sensing scheduling scheme based on discrete particle swarm optimization algorithm is superior to random scheduling scheme and greedy scheduling scheme based on the SNR, which gets a higher spectrum sensing accuracy.