粒子群算法在协同通信功率分配优化中的应用

Application of Particle Swarm Optimization in the Optimal Power Allocation of Cooperative Communications

研究通信优化系统性能,在协同通信中,源节点和中继节点的功率分配对系统的性能有着重要影响,存在分配不合理的问题,系统将达不到理想性能。为了优化功率分配,提出协同通信方式进行优化分配功率。根据粒子群算法在资源分配和函数优化中的优越性,分别针对放大前向和译码前向协同模式,在总功率一定的条件下,以大信噪比时的误码率的下界或上界作为粒子群优化算法的目标函数,优化源节点和中继节点的功率分配。通过仿真验证,在平坦衰落信道条件下,粒子群算法优化出的功率分配比平均分配功率时的误码率有了明显下降,提高通信系统和性能。

In cooperative communications,the power allocation of source nodes and relay nodes will affect the performance of the system essentially.If the allocation is unreasonable,the performance of the system will be unideal,so the optimal power allocation is very important to cooperative communications.Based on the superiority of particle swarm optimization（PSO） in the resource allocation and function optimization and on the assumption of constant total transmit power,an optimal power allocation scheme between source nodes and relay nodes is proposed in the amplify-and-forward（AF） model and the decode-and-forward（DF） model,using the lower bound or upper bound of bit error rate（BER） in high SNR as objective function of PSO.The result of simulation through MATLAB shows that,in flat fading channels,the BER of the optimal power allocation scheme through PSO is obviously lower than that of the average power allocation scheme.