Joint MIMO channel tracking and symbol detection with EM algorithm and soft decoding

Fu-Hsuan Chiu, Sau-Hsuan Wu, C.-C. Jay Kuo
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引用次数: 3

Abstract

An expectation maximization (EM) algorithm for joint channel tracking and symbol detection in a multi-input multi-output (MIMO) time-varying frequency-selective fading environment is proposed in this research. Based on the recursive EM procedure in conjunction with soft decoding, we develop an iterative algorithm that performs the minimum mean squared error (MMSE) channel estimation and the maximum a posterior (MAP) probability symbol detection jointly. Two soft decoders are examined; namely, the BCJR algorithm and the soft sphere decoder. The performance of the proposed algorithm is evaluated via simulation and compared with that of Kalman filtering with hard decision feedback. It is demonstrated by numerical simulation that the proposed algorithm has robust performance in the presence of a severe channel model mismatch
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基于EM算法和软解码的MIMO信道跟踪和符号检测
针对多输入多输出(MIMO)时变选频衰落环境下的联合信道跟踪和符号检测问题,提出了一种期望最大化算法。基于递归电磁过程与软译码相结合,我们开发了一种迭代算法,该算法同时进行最小均方误差(MMSE)信道估计和最大后验(MAP)概率符号检测。研究了两种软解码器;即BCJR算法和软球解码器。通过仿真对该算法的性能进行了评价,并与带有硬决策反馈的卡尔曼滤波进行了比较。数值仿真结果表明,该算法在信道模型严重失配的情况下具有良好的鲁棒性
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