混合粒子群优化算法在CDMA系统多用户检测中的应用

针对粒子群优化算法易早熟的问题，提出了一种混合粒子群优化算法(HPSO)。首先在算法中采用惯性权重的分段递减策略，以提高算法的全局搜索能力；然后在算法后期，引入拉伸技术剔除比局部极值大的点，缩小搜索空间，使算法能及时跳出局部最优从而加速收敛，最后提出了基于HPSO算法的多用户检测器。仿真结果表明在信噪比相同的条件下，该多用户检测器的误码率和抗远近效应性能更接近于最佳多用户检测器，有效解决了码分多址通信系统中的多址干扰问题。

Application of hybrid particle swarm optimization in CDMA multiuser detection

For the Particle Swarm Optimization(PSO) algorithm prematurity problem,a hybrid particle swarm optimization(HPSO) algorithm is proposed.Firstly, the algorithm uses a segmental descending inertia weight strategy to improve the global search ability.Then, in the later algorithm,stretching technique is introduced to eliminate the points larger than the local extremum and narrow the search space,so that the algorithm can jump out of local optimum in time and accelerate convergence. Finally,a multiuser detector based on HPSO algorithm is proposed. The simulation results show that under the same signal-to-noise ratio(SNR) condition, the bit-error rate(BER) and near-far resistance performance of this multiuser detector are closer to that of the optimal multiuser detector(OMD), and it effectively solves the problem of multi-access interference in CDMA communication system.