混沌拟态物理优化的认知频谱差异分配

针对认知无线电网络的频谱分配问题,提出了一种考虑频谱可用率的分配模型,并在约束处理时,将可用率更高的频谱分配给认知用户;基于频谱分配问题的NP(非确定性多项式)特性,进而提出了一种基于混沌拟态物理优化的智能算法。使用混沌的遍历性初始化种群,改进了微粒的作用力方程,避免算法陷入局部最优。仿真实验结果表明:该算法能获得更高的网络收益,提高了频谱使用效率。

Spectrum difference allocation of cognitive radio network based on chaotic artificial physics optimization

Focusing on the spectrum allocation problem in cognitive radio network, an allocation model considering spectrum availability was proposed. When handling the constraint, the higher availability spectrum was assigned to the cognitive users. A chaotic artificial physics optimization was proposed based on NP (Non-deterministic Polynomial) feature of spectrum allocation problem. The ergodicity of chaos was used to initiate population and the force equation between particles was improved to avoid the algorithm falling into local optimum. The simulation results show that the proposed algorithm can get better network revenue and improve the spectrum usage.