For the problem of algorithm convergence rate low and algorithm convergence time long in mobile communication frequency spectrum allocation process, we presented double particle swarm algorithm based on selectivity mutation (SM-DPSO), and it is used to resolve frequency spectrum allocation problem. Proposed algorithm divided the particle swarm into two subgroups, the two subgroups is updated by different update strategies, the algorithm is easy to jump out of local optima solution;The single particle is introduced selectivity mutation, it increased population diversity and the convergence speed. Simulation results shown that: the SM-DPSO algorithm can be better to solve the wireless channel allocation problem, it improved the convergence rate and convergence speed of algorithm.%针对移动通信频率分配过程中已有算法存在收敛率低和算法收敛时间长的问题，提出了基于选择性变异（SM-DPSO）的双粒子群优化算法，并用于解决频率分配问题。提出算法将粒子群划分为两个子群采用不同的更新策略，使算法易跳出局部最优解；对单个粒子进行选择性变异，提高了种群多样性的同时加快了算法的收敛速度。仿真结果表明：SM-DPSO能较好的解决移动通信的频率分配问题，提高了算法的收敛率和收敛速度。
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