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基于子空间盲多用户检测算法的设计和仿真

             

摘要

With the rapid development of mobile communication techonology, CDMA (Code Division Multiple Access) as core techonology of the third generation of mobile communication becomes entering into peoples common life. CDMA has the advantage of large capacity, soft capacity and anti-multipath fading, but the existence of MAI ( Multiple Access Interference ) has serious impact on system performance and capacity. So how to eliminate and control this kind of interference becomes one hot topic of CDMA research. Third-generation mobile communication system has multi-user detection (MUD) to overcome the multiple access interference as one of the effective ways. This paper mainly researches on the direct sequence and spread spectrum code division multiple access ( DS-CDMA) system in the blind multiuser detection algorithm, deeply researches on the multi-user detection based on the constant modulus blind adaptive Kalman filtering algorithm. The method that Kalman filter algorithm introduced subspace improved Kalman filtering algorithm efficiency.%随着数字移动通信技术的飞速发展,以码分多址(CDMA)为核心的第三代移动通信(3G)技术已经走入人们的日常生活.CDMA系统具有容量大、软容量、抗多径衰落强等优点,但多址干扰(MAI)的存在却严重的影响了系统的性能和容量,因此如何消除和抑制这种干扰就成了CDMA技术研究的热门话题之一,第三代移动通信系统已经将多用户检测技术(MUD)作为克服多址干扰的有效方法之一.文中主要研究了直接序列扩频码分多址( DS - CDMA)系统中的盲多用户检测算法,深入的研究了基于卡尔曼滤波的盲多用户检测算法,通过在卡尔曼滤波算法上引入子空间提高了原有卡尔曼滤波算法的效率.

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