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Adaptive DFE Multiuser Receiver for CDMA Systems using Two-Step LMS-Type Algorithm: An Equalization Approach

机译:使用两步LMS类型算法的CDMA系统自适应DFE多用户接收器:一种均衡方法

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摘要

This paper presents an adaptive decision feedback equalizer (DFE) based multiuser receiver for code division multiple access (CDMA) systems over smoothly time-varying multipath fading channels using the two-step LMS-type algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh-distributed tap coefficients. The receiver uses an adaptive minimum mean square error (MMSE) multiuser channel estimator based on the reduced Kalman least mean square (RK-LMS) algorithm to predict these tap coefficients (Kohli and Mehra, Wireless Personal Communication 46:507–521, 2008). We propose the design of adaptive MMSE feedforward and feedback filters by using the estimated channel response. Unlike the previously available Kalman filtering algorithm based approach (Chen and Chen, IEEE Transactions on Signal Processing 49:1523–1532, 2001), the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser receiver. The computer simulation results are presented to show the substantial improvement in its bit error rate performance over the conventional LMS algorithm based receiver. It can be inferred that the proposed multiuser receiver proves to be robust against the nonstationarity introduced due to channel variations, and it is also beneficial for the multiuser interference cancellation and data detection in CDMA systems.
机译:本文提出了一种基于自适应决策反馈均衡器(DFE)的多用户接收机,用于采用两步LMS型算法在平滑时变多径衰落信道上进行码分多址(CDMA)系统。频率选择衰落信道被建模为具有平稳时变瑞利分布抽头系数的抽头延迟线滤波器。接收器使用基于减少的卡尔曼最小均方(RK-LMS)算法的自适应最小均方误差(MMSE)多用户信道估计器来预测这些抽头系数(Kohli和Mehra,无线个人通信46:507-521,2008) 。通过使用估计的信道响应,我们提出了自适应MMSE前馈和反馈滤波器的设计。与以前可用的基于Kalman滤波算法的方法(Chen和Chen,IEEE Transactions on Signal Processing 49:1523–1532,2001)不同,RK-LMS算法的结合降低了多用户接收机的计算复杂性。给出的计算机仿真结果表明,与传统的基于LMS算法的接收机相比,其误码率性能有了实质性的提高。可以推断出,所提出的多用户接收机被证明对由于信道变化而引起的非平稳性具有鲁棒性,并且对于CDMA系统中的多用户干扰消除和数据检测也是有益的。

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