【摘要】 提出并讨论了两种实现码分多址（ＣＤＭＡ）系统中最佳多用户检测（ＭＵＤ）的神经网络方法。一种基于离散ＨｏＰｆｉｅｌｄ神经网络（ＤＨＮＮ），另一种基于采用反向传播（ＢＰ）算法的多层感知器（ＭＬＰ）神经网络（ＢＰＮＮ）。理论分析和计算机模拟都证实了这两种神经网络方法的可行性、优越性和实用性。前者适用“固定”用户情况；后者既可用于“固定”用户情况也适用于移动用户情况，因而在未来的ＣＤＭＡ个人通信网（ＰＣＮ）中有较好的应用前景。更多还原

【Abstract】 Two neural networks for implementing optimum multiuser detector (MUD) in code division multiple access(CDMA) channels are discussed. One is based on discrete Hopfield neural network (DHNN),andthe other is based on multilayer perceptron network using back propagation algorithms (BPNN), which areverified by theoretical analysis and computer simulation. The former is suitable for the case that the users inthe system are not mobile, while the later iS suitable for the case that the users might be mobile, such as in CDMA personal communication networks (PCN).更多还原