动态环境下基于粒子群算法的多用户检测器

在动态环境下，在线用户数和用户的参数都是随时间变化的。研究表明，在动态环境下首先识别在线用户，然后进行多用户检测，会极大地提高多用户检测器的性能和节省资源。基于随机集理论（Random Set Theory，RST）理论，应用一种群智能算法——粒子群算法（Particle Swarm Optimization，PSO）提出了动态环境下的多用户检测器。仿真结果表明该检测器收敛速度快、适应性较强，有效地解决了动态环境下多用户检测。

Multiuser detection in dynamic environment based on particle swarm optimization algorithm

In Dynamic Environment (DE),the number of active users,their locations,as well as the parameters that characterize their channel states,vary with time.Proved by several authors,identifying active users and using this information will cause signifi-cant performance improvement of Multiuser Detection (MUD).By using the Random Set Theory (RST),a MUD in DE based on Particle Swarm Optimization (PSO) is presented.Simulation results show that the detector has good performance on optimization and efficient adaptabi...