种群递减-变异蚁群算法在多用户检测中的应用  

Population Declining-mutation Ant Colony Optimization Algorithm and its Application in Multiuser Detection

作　　者：任广辉[1] 吴晨光[1] 赵楠[1] 王凤[1] 

机构地区：[1]哈尔滨工业大学电子与信息技术研究院,黑龙江哈尔滨150001

出　　处：《计算机测量与控制》2009年第11期2289-2291,共3页Computer Measurement &Control

摘　　要：蚁群算法(ACO)解决组合优化问题有着优良的性能,但由于信息素的不断积累,容易陷入早熟收敛,不能得到全局最优解,为了克服这个缺点,把种群递减机制和遗传算法中的变异机制引入ACO,提出了种群递减-变异蚁群算法(PDMACO),然后将PD-MACO应用到多用户检测中;仿真结果证明,PDMACO多用户检测器在抗多址干扰和远近效应能力方面远优于ACO多用户检测器,并接近于最优多用户检测器。Ant colony optimization （ACO） algorithm has already successfully been used in discrete optimization, however, as the phenomona accumulates, we may not get a global optimum because it stops searching early. To resolve the problem, a novel algorithm called Popu- lation Declining--Mutation Ant Colony Optimization （PDMACO） is proposed by introducing population declining mechanism and mutation mechanism of Genetic Algorithms （GA） to ACO. Then PDMACO is applied to multiuser detection and simulation results show that the per- formance of PDMACO multiuser detector in reducing the bit-error rate and near-far effect is much better than that of ACO multiuser detector and is also close to the performance of optimal multiuser detector.

关 键 词：码分多址 多用户检测 蚁群算法 种群递减机制 变异机制 

分 类 号：TP87[自动化与计算机技术—检测技术与自动化装置]