基于免疫量子算法的多用户检测技术研究

基于免疫算法和新的遗传量子算法,在码分多址通信系统中提出了一种解决多用户检测问题的进化计算方法--免疫量子算法(IQA).在IQA中,随机Hopfield神经网络被用于制作疫苗去提高IQA的收敛速度.另外,IQA为随机Hopfield神经网络提供良好的初始解会提高制作疫苗的性能,进一步改善每一代中量子种群中的适应度.通过在DS-CDMA系统进行Monte Carlo仿真,IQA算法的有效性和可行性被证实.仿真结果表明所提的IQA检测器的误码率性能优于其他的次优检测器,接近于最优检测器的理论下限.

Multiuser detection technology based on an immune quantum algorithm

A novel evolutionary computational method,called an immune quantum algorithm(IQA),is proposed for the multiuser detection of code division multiple access(CDMA) systems on the basis of the immune algorithm and the newly developed genetic quantum algorithm(NGQA).In the IQA,the stochastic Hopfield neural network was used to make a vaccine to improve the convergence rate of the IQA.In addition,the IQA could provide a good initial solution for a stochastic Hopfield neural network to improve the performance of the vaccine,leading to an improvement in the fitness of the quantum population in each generation.The effectiveness and the applicability of IQA were demonstrated by a Monte Carlo simulation in direct sequence code division multiple access(DS-CDMA) systems.The simulation results show that the proposed IQA-based detector is superior to other suboptimal detectors in bit error rate,approaching the theoretical lower bound of the optimal detector.