Abstract: With respect to the premature convergence and slow convergence rate of Adaptive Genetic Algorithms Multiuser Detector（AGA-MUD），applied the nonlinear Sigmoid function to the adaptive genetic algorithms and combined the resisted multiple-access interference performance of decorrelation algorithms，a new Multi-User Detector based on Improved Adaptive Genetic Algorithms and Decorrelation algorithm（IAGAD-MUD） is proposed.Simulation results show that IAGAD-MUD is better than AGA-MUD and Simple Genetic Algorithms Multi-User Detector（SGA-MUD） not only in resisting multiple-access interference and near-far effects，but also in capacity of system.

摘要： 针对自适应遗传算法在多用户检测应用中容易早熟收敛和速度慢的问题，将非线性Sigmoid函数应用于自适应遗传算法并结合解相关算法的抗多址干扰能力，提出了一种基于改进自适应遗传算法和解相关算法的多用户检测器。实验仿真结果表明：该多用户检测器的检测性能，不论在抗多址干扰和远近效应方面还是在系统用户容量方面，都明显优于自适应遗传算法多用户检测器和简单遗传算法多用户检测器。