基于离散人工蜂群算法的认知无线电频谱分配

针对二进制粒子群优化算法在认知无线电频谱分配中容易陷入局部最优等问题，将人工蜂群算法引入到认知无线电频谱分配中，提出了基于离散人工蜂群算法的认知无线电频谱分配方法。针对一种认知无线电网络模型，将离散人工蜂群算法中的蜜源位置离散化，与模型中的可用频谱矩阵相结合产生分配矩阵，对目标函数进行优化，并且使用了一种新的比例公平性目标函数评价该算法的性能；通过仿真比较了本文算法与二进制粒子群优化算法的频谱分配方法的性能，同时在使用电视频段的认知无线电系统进行了验证，结果表明本文算法的高效性和优越性。

Cognitive radio spectrum allocation based on discrete artificial bee colony algorithm

In order to avoid the defect that spectrum allocation based on Binary Particle Swarm Optimization algorithm in cognitive radio is easy to trap into a local optimization. Cognitive radio spectrum allocation based on discrete artificial bee colony algorithm (DABC) is presented. For a given cognitive radio network topology model, the randomly generated food source positions are transformed to discrete states by a sigmoid function. The channel allocation matrix is obtained based on discrete food source positions and the channel availability matrix, and then the objective function is optimized. In addition, a new fairness objective function is used to evaluate the performance of the algorithms. The high efficiency and superiority of the discrete artificial bee colony algorithm are demonstrated in the TV band.