【摘要】 针对电力线通信系统中应用传统粒子群算法进行比特功率分配存在陷入局部最优值和收敛速度慢的问题,提出了IPSO(improved particle swarm optimization)算法.新算法通过引入遗传算法的交叉和变异操作,克服了传统粒子群算法由早熟收敛而陷入局部最优解的问题,加快了收敛速度.建立了IPSO算法的理论模型,给出了新算法在PLC-OFDM系统中进行比特功率分配的方法.仿真结果表明,在PLC-OFDM系统中应用IPSO算法进行比特功率分配与GA算法和传统粒子群算法相比,可以加快收敛速度,改善系统的信噪比特性,降低系统发射功率.更多还原

【Abstract】 In view of the traditional particle swarm optimization algorithm for bit and power allocation existing problems of getting local optimum solution and slow convergence speed in power line communication system,IPSO( Improved Particle Swarm Optimization) algorithm has been proposed. This algorithm,by introducing crossover and mutation operations of genetic algorithm,overcomes the problem of the traditional particle swarm algorithm into local optimal solution due to premature convergence,and speeds up the convergence. The theoretical model of IPSO algorithm is constructed,and the method of applying the new algorithm in PLC-OFDM system was presented as well. Simulation results show that compared with Genetic Algorithm and traditional PSO algorithm,using IPSO algorithm for bit power allocation in PLC-OFDM system can speed up convergence,improve the SNR characteristic of the system and reduce the transmission power.更多还原