MIMO系统中改进的二进制粒子群天线选择算法

在多输入多输出系统中，发射端和接收端的多天线配置提高了信道容量和传输可靠性，而天线选择技术能在保持系统优点的同时有效地降低运算复杂度以及硬件成本。为了能在时变的信道条件下快速地选择出一组最优的天线子集，提出了一种基于二进制粒子群算法的改进的天线选择算法。推导出了二进制粒子群联合收发端天线选择的信道容量公式，并将其作为粒子群算法的适应度函数，使天线选择问题转换成二进制编码串的组合优化问题。通过改进模糊函数提高粒子群算法的收敛性，让二进制粒子群尽可能地收敛于全局最优位置。仿真结果表明，改进的算法能在降低运算复杂度的同时提高收敛性，且系统信道容量趋近于最优算法。

An improved binary particle swarm optimization antenna selection algorithm in MIMO systems

In Multiple-Input Multiple-Output(MIMO) systems,multiple antenna configurations at the transmitter and receiver improve channel capacity and transmission reliability.The antenna selection technology can effectively reduce the computational complexity and hardware costs while maintaining the advantages of the system.In order to quickly select a set of optimal antenna subsets under the time-varying channel conditions,an improved antenna selection algorithm based on the binary particle swarm optimization(BPSO) algorithm is proposed.The channel capacity formula for antenna selection of BPSO joint transceiver is deduced and taken as the fitness function of the particle swarm optimization(PSO) algorithm,so that the antenna selection problem can be transformed into the combinatorial optimization problem of binary coding string.The algorithm improves the convergence of the PSO algorithm by improving the fuzzy function,so that the binary particle swarm converges to the global optimal position as far as possible.The simulation results show that the improved algorithm can reduce the computational complexity and improve the convergence,and the system channel capacity approaches that of the optimal algorithm.