Doubly dispersive channel estimation with scalable complexity

M. Simko, C. Mehlführer, M. Wrulich, M. Rupp
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引用次数: 65

Abstract

In this paper, we present an Approximate Linear Minimum Mean Square Error (ALMMSE) fast fading channel estimator for Orthogonal Frequency Division Multiplexing (OFDM). The ALMMSE channel estimator utilizes the knowledge of the structure of the autocorrelation matrix given by the Kronecker product between the time correlation matrix and the frequency correlation matrix. We separate the Linear Minimum Mean Square Error (LMMSE) filtering matrix into two matrices corresponding to individual filtering in frequency and time. The eigenvalues of these two matrices are rank-one approximated by the eigenvalues of the LMMSE filtering matrix. The complexity of the ALMMSE estimator can be scaled by varying the number of the considered number of eigenvalues. Simulation results show that the proposed ALMMSE channel estimator looses only 0.1 dB compared to the LMMSE channel estimator in realistic scenarios.
具有可扩展复杂度的双频散信道估计
本文提出了一种近似线性最小均方误差(ALMMSE)的正交频分复用(OFDM)快速衰落信道估计方法。ALMMSE信道估计器利用了由时间相关矩阵和频率相关矩阵之间的Kronecker积给出的自相关矩阵的结构知识。我们将线性最小均方误差(LMMSE)滤波矩阵分离为两个矩阵,分别对应于频率和时间上的单独滤波。这两个矩阵的特征值由LMMSE滤波矩阵的特征值进行秩一逼近。ALMMSE估计器的复杂度可以通过改变所考虑的特征值的个数来缩放。仿真结果表明,在实际情况下,与LMMSE信道估计器相比,所提出的ALMMSE信道估计器的信道损失仅为0.1 dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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