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Adaptive array beamforming under Rayleigh fading environment

机译:瑞利衰落环境下的自适应阵列波束成形

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摘要

Beamforming is a signal processing technique used for directional signal transmission or reception. Without moving the individual elements of the antenna array physically, the array pattern can be steered in particular direction by adjusting the amplitude and phase, called weights of the signal. Several signal processing techniques are used to adjust the weights, which demonstrate the self steering capability of adaptive antenna array. But those techniques exhibit a trade off between the convergence rate and the mean square error. This paper explains a novel adaptive technique, called dual stage least mean square algorithm, which is able to track the desired signal amid the interfering signals and noise, even for low input signal-to-noise ratio (SNR). The simulation results show that the performance of dual stage LMS algorithm is better in terms of convergence, mean square error, error vector magnitude than the earlier least mean square (LMS) technique. These techniques are compared and verified using MATLAB.
机译:波束成形是一种用于定向信号传输或接收的信号处理技术。在不物理移动天线阵列的各个元件的情况下,可以通过调节幅度和相位(称为信号权重)来在特定方向上控制阵列方向图。几种信号处理技术用于调整权重,这些技术证明了自适应天线阵列的自转向能力。但是这些技术在收敛速度和均方误差之间表现出折衷。本文介绍了一种新颖的自适应技术,称为双级最小均方算法,即使在低输入信噪比(SNR)的情况下,该技术也能够在干扰信号和噪声中跟踪所需信号。仿真结果表明,与较早的最小均方(LMS)技术相比,双级LMS算法在收敛性,均方误差,误差矢量幅值方面的性能更好。使用MATLAB对这些技术进行了比较和验证。

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