基于PSO-GA算法的多用户OFDM系统资源分配  

Resource Allocation for Multiuser OFDM System based on PSO-GA Algorithm

作　　者：梅金平[1] 张士兵[1] 王海莲[1] 

机构地区：[1]南通大学电子信息学院,江苏南通226019

出　　处：《电视技术》2014年第1期115-119,共5页Video Engineering

基　　金：国家自然科学基金资助项目(61071086);江苏省普通高校研究生科研创新计划项目(CXZZ12_0866);南通大学自然科学研究项目(11Z061);南通大学研究生科技创新计划项目(YKC12069)

摘　　要：为了最小化多用户OFDM系统的总发射功率，提出利用改进的粒子群算法与遗传算法相结合的联合算法（PSO—GA）来搜索最优的子载波和比特分配。该算法首先利用改进粒子群算法对系统的子载波和比特分配进行优化。算法运行过程中，当更新后的粒子速度大于最大粒子速度或小于最小粒子速度时，取最大粒子速度与最小粒子速度区间中的一个随机值作为更新的粒子速度。待PSO—GA算法的改进粒子群算法收敛后，将收敛后的种群作为遗传算法的初始种群，再利用遗传算法进行系统的子载波和比特优化分配，进而得出最优解。仿真结果表明，利用该算法比利用遗传算法、粒子群算法与Zhang算法的分配方案使系统需要的总发射功率降低2～10dB。To minimize the total trmasmitting power in multiuser Orthogonal Frequency Division Multiplexing （OFDM） system, an algorithm combined improved particle swarm optimization algorithm and genetic algorithm（PSO-GA）is proposed to optimize the subcarriers and bit allocation. In the algo- rithm ,the improved particle swarm optimization algorithm is used to optimize the system subcarriers and bit allocation first. When the particle velocity up- dated is bigger than the maximum particle velocity or smaller than the minimum particle velocity, a random value between the maximum particle velocity and the minimum particle velocity is taken as the updating particle velocity. When the algorithm has converged ,take the convergence populations as the initial population of the genetic algorithm. Then,the genetic algorithm is used to optimize the system subearriers and bit allocation again and the optimal solution is obtained. The simulation results show that the proposed algorithm overcomes the genetic algorithm, particle swarm optimization algorithm and Zhang algorithm 2 - 10 dB in transmitted power.

关 键 词：正交频分复用 粒子群和遗传联合算法 子载波分配 比特分配 

分 类 号：TN914[电子电信—通信与信息系统]