CAJ | 학술논문

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.
재동태배경하,재선용호수화용호적삼수도시수시간변화적.연구표명,재동태배경하수선식별재선용호,연후진행다용호검측,회겁대지제고다용호검측기적성능화절성자원.기우수궤집이론(Random Set Theory,RST)이론,응용일충군지능산법--입자군산법(Particle Swarm Optimization,PSO)제출료동태배경하적다용호검측기.방진결과표명해검측기수렴속도쾌、괄응성교강,유효지해결료동태배경하다용호검측.
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 significant performance improvement of Muhiuser 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 adaptability.