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将多用户MIMO下行链路调度问题描述为一优化问题,并引入粒子群优化(particle swarm optimization,PSO)算法进行求解.针对容量和复杂度有不同要求的应用场合,给出了两类采用不同目标函数PSO调度算法:基于容量PSO(C-PSO)调度算法和基于特征值下界PSO(LBE-PSO)调度算法.C-PSO算法目标是获得接近最优容量的性能;而LBE-PSO算法旨在有效降低算法复杂度的同时尽可能获得高的容量增益.进一步,从粒子和速度两方面对PSO算法的收敛性进行分析并得出收敛条件,然后通过不同参数值的实例对其进行验证.仿真结果表明,C-PSO算法能够以较低的复杂度获得接近穷搜索算法的容量,而LBE-PSO调度算法则提供了一种能够在容量和复杂度之间很好折中的调度方案.
The multi-user MIMO downlink scheduling problem is described as an optimization problem, and particle swarm optimization (PSO) algorithm is introduced to solve the problem.For the applications with different requirements of capacity and complexity, The objective function PSO scheduling algorithm is based on capacity PSO (C-PSO) scheduling algorithm and eigenvalue-based lower bound PSO (LBE-PSO) scheduling algorithm. The goal of C-PSO algorithm is to obtain the performance close to the optimal capacity. So as to reduce the complexity of the algorithm and obtain a high capacity gain as much as possible.Furthermore, the convergence of the PSO algorithm is analyzed from the aspects of particle and speed, and the convergence condition is obtained. Then the examples are validated by different parameter values. The simulation results show that the C-PSO algorithm can obtain the capacity close to the poor search algorithm with lower complexity, while the LBE-PSO scheduling algorithm provides a scheduling scheme that can compromise between capacity and complexity.