利用深度神经网络实现毫米波大规模多输入多输出系统的信道估计和先导减少

IF 4.1 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

ICT Express Pub Date : 2024-08-01 DOI:10.1016/j.icte.2024.02.003

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引用次数: 0

摘要

本文针对毫米波点对点多输入多输出系统，提出了基于深度学习的信道估计和先导缩减方案。所提方案包括两个步骤，第一步是应用去噪自动编码器进行信道估计。利用自动编码器的去噪特性，可以进行稀疏信道估计，尽管由于先导序列较短，先导序列的正交性得不到保证。第二步是利用信道的时间相关性，利用先前的估计提取当前估计的信息。通过仿真，所提出的方案在减少先导序列的情况下表现出卓越的性能。

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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Channel estimation and pilot reduction for mmWave massive MIMO systems using deep neural networks

In this paper, we propose deep learning-based channel estimation and pilot reduction for mmWave point-to-point multi-input multi-output systems. The proposed scheme consists of a two-step approach where the first step is applying a denoising autoencoder for channel estimation. With the denoising characteristic of autoencoder, sparse channel estimation can be conducted although the orthogonality of pilot sequences is not guaranteed due to shorter pilots. The second step is exploiting the temporal correlation of the channel, using the previous estimate to extract information for the current estimate. Through simulation, the proposed scheme shows superior performance with reduced pilots.

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来源期刊

ICT Express Multiple-

CiteScore

10.20

自引率

1.90%

发文量

167

审稿时长

35 weeks

期刊介绍： The ICT Express journal published by the Korean Institute of Communications and Information Sciences (KICS) is an international, peer-reviewed research publication covering all aspects of information and communication technology. The journal aims to publish research that helps advance the theoretical and practical understanding of ICT convergence, platform technologies, communication networks, and device technologies. The technology advancement in information and communication technology (ICT) sector enables portable devices to be always connected while supporting high data rate, resulting in the recent popularity of smartphones that have a considerable impact in economic and social development.