频率选择性衰落MIMO信道和信道Rice因子估计

S. Moghaddam, H. Nooralizadeh
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引用次数: 2

摘要

为了估计多输入多输出(MIMO)信道,提出了移位比例最小二乘(SSLS)和一般形式的线性最小均方误差(GLMMSE)信道估计器。结果表明,与瑞利估计器相比,这些估计器在频率选择性衰落MIMO信道中获得了更好的最小可能贝叶斯cram - rao下界(CRLBs)。数值算例表明,这些估计器的性能对信道Rice因子的准确估计并不敏感。此外,为了估计接收机的信道赖斯因子,我们提出了两种基于最小二乘估计和训练序列的新算法。仿真结果验证了这些算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Frequency selective Rician fading MIMO channel and channel Rice factor estimation
In this paper, to estimate Rician frequency selective fading Multiple-Input Multiple-Output (MIMO) channels, the Shifted Scaled Least Squares (SSLS) and General form of the Linear Minimum Mean Square Error (GLMMSE) channel estimators are proposed. It is shown that these estimators achieve much better minimum possible Bayesian Cramér-Rao Lower Bounds (CRLBs) in the frequency selective Rician fading MIMO channels compared with those of the Rayleigh one. Numerical examples show that the performance of these estimators is not more sensitive to accurate estimation of the channel Rice factor. Furthermore, to estimate the channel Rice factor at the receiver, we propose two new algorithms which perform based on the Least Squares (LS) estimates and training sequences. Simulation results confirm the efficiency of these algorithms.
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