Neural Network compensator based MMSE receiver for HPA nonlinearity in MIMO OFDM systems

M. Dakhli, R. Zayani, R. Bouallègue
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引用次数: 4

Abstract

In this paper, we present a method based on Neural Network (NN) technique and accompanied with MMSE (Minimum Mean Square Error), which corrects at the receiver level, the Non-Linear (NL) distortions due to the HPA (High Power Amplifier). The neural network consists on a feed-forward Multi-Layer Perceptron (MLP) associated with Levenberg-Marquardt learning algorithm. The results show that the neural network compensator brings perceptible in a complete VBLAST MIMO OFDM (Vertical Bell Laboratories Layered Space-Time Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing) system running under a Rayleigh fading channel.
基于神经网络补偿器的MMSE接收机用于MIMO OFDM系统中HPA非线性
在本文中,我们提出了一种基于神经网络(NN)技术并伴有最小均方误差(MMSE)的方法,该方法可以在接收机级校正由HPA(高功率放大器)引起的非线性(NL)失真。该神经网络由前馈多层感知器(MLP)和Levenberg-Marquardt学习算法组成。结果表明,在瑞利衰落信道下运行的VBLAST MIMO OFDM(垂直贝尔实验室分层空时多输入多输出正交频分复用)系统中,神经网络补偿器具有良好的可感知性。
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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