V-BLAST系统中有效的近优检测方法

在离散粒子群算法的基础上,结合遗传算法中的变异算子,提出了一种新的离散粒子群优化算法,进而设计了一种使用新的离散粒子群优化算法和并行干扰抵消算法相结合的垂直分层空时系统检测方法。该方法将NDPSO和PIC有机结合可以改善NDPSO的性能,同时为了进一步加快NDPSO的收敛速度,将迫零检测结果作为NDPSO的初始值。分析和仿真结果表明,所提出的检测方法与最优检测方法相比有更低的计算复杂度,与次优检测方法相比具有更好的误码率性能,为寻求新的V-BLAST系统检测算法提供了思路。

Efficient near-optimal detection method for V-BLAST systems

According to discrete particle swarm optimization(DPSO) and combining DPSO with the mutation operator of the genetic algorithm,a new discrete particle swarm optimization(NDPSO) algorithm is proposed.Then a detection method that employs NDPSO and parallel inference cancellation(PIC) algorithm in vertical bell-labs layered space-time(V-BLAST) systems is proposed.Such a hybridization of the NDPSO with the PIC can further improve the performance of the NDPSO.To speed up the convergence of the NDPSO,the zero force(ZF) output is used as an initial particle position of the NDPSO.Analyses and simulation results show that the proposed detection method has lower computational complexity than the optimal detection approach and has better detection performance than the suboptimal detection approaches,and is also a good idea for finding a new method to solve the detection problem in V-BLAST systems.