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Channel Estimation and Data Detection with Fuzzy C-Means Based EM Approach in MIMO System

机译:MIMO系统中基于模糊C-均值EM方法的信道估计和数据检测

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Classical wireless communication technologies are threatened with so many challenges for meeting the desires of ubiquity and mobility for the cellular systems. Hostile wireless channels features and restricted frequency bandwidths are obstacles in future generation systems. In order to deal with these limitations, different advanced signal processing approaches, such as expectation-maximization (EM) algorithm, SAGE algorithm, Baum-Welch algorithm, Kalman filters and their extensions etc. were proposed. In this paper, estimation of unknown channel parameter and detection of data at receiver end has been performed. MIMO Rayleigh and Rician channels are taken for wireless communication. To find the initial point for EM algorithm FCM clustering algorithm is used. In this work, algorithm is implemented using MATLAB R2012a. The performance matrices of the algorithm are bit error rate (BER) and mean square error (MSE) at different values of signal to noise ratio.
机译:为了满足蜂窝系统的普遍性和移动性的需求,古典无线通信技术面临许多挑战。敌对的无线信道功能和受限的频率带宽是下一代系统的障碍。为了克服这些局限性,提出了不同的高级信号处理方法,如期望最大化(EM)算法,SAGE算法,Baum-Welch算法,卡尔曼滤波器及其扩展等。在本文中,已经进行了未知信道参数的估计和接收器端的数据检测。 MIMO Rayleigh和Rician信道用于无线通信。为了找到EM算法的起点,使用了FCM聚类算法。在这项工作中,算法是使用MATLAB R2012a实现的。该算法的性能矩阵是不同信噪比值下的误码率(BER)和均方误差(MSE)。

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