Adaptive channel estimation and tracking for indoor MIMO OFDM mobile communication systems

S. S. Sarnin, S. M. Sulong, N. Ya'acob
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引用次数: 3

Abstract

This paper highlights the performance of the proposed EW-RLS and NLMS channel estimator is evaluated by means of simulation, in the context of communication system with multiple antenna operating in indoor environments. A focus is given to the capabilities of these algorithms to track the time-variations of the channel at different training rates and different Doppler frequencies. Three adaptive algorithms are considered; namely the least squares (LS), the recursive least squares (RLS) algorithm and the least mean square (LMS) algorithm. The RLS is a widely used algorithm in channel estimation, especially when the channel is a slow time-varying. This algorithm has the property of fast convergence compared to the LMS algorithm at the cost of little increase in the computational complexity. The performance is evaluated in terms of the MSE of the channel estimate, and the system BER, for different Doppler frequencies (correspond to different mobility speeds). Simulation results have demonstrated that time-domain adaptive channel estimation and tracking in MIMO OFDM systems based on the DD EW-RLS and DD-NLMS is very effective in slowly to moderate time-varying fading channels. This paper provides analysis, evaluation and computer simulations in MATLAB.
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室内MIMO OFDM移动通信系统的自适应信道估计与跟踪
本文重点介绍了在室内多天线通信系统环境下,采用仿真方法对EW-RLS和NLMS信道估计器的性能进行了评估。重点讨论了这些算法在不同训练速率和不同多普勒频率下跟踪信道时变的能力。考虑了三种自适应算法;即最小二乘(LS)算法、递推最小二乘(RLS)算法和最小均方差(LMS)算法。RLS是一种广泛应用于信道估计的算法,特别是在信道是慢时变的情况下。与LMS算法相比,该算法收敛速度快,但计算量增加较少。在不同的多普勒频率(对应于不同的移动速度)下,根据信道估计的MSE和系统误码率来评估性能。仿真结果表明,基于DD EW-RLS和DD- nlms的MIMO OFDM系统时域自适应信道估计和跟踪在慢至中度时变衰落信道中是非常有效的。本文在MATLAB中进行了分析、评价和计算机仿真。
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