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在使用低密度奇偶校验(LDPC)码的迭代均衡和解码系统中对存在码间干扰(ISI)的加性高斯白噪声(AWGN)信道的脉冲响应估计

Estimation of the Impulse Response of the AWGN Channel with ISI within an Iterative Equalization and Decoding System That Uses LDPC Codes.

作者信息

Cuc Adriana-Maria, Morgoș Florin Lucian, Grava Adriana-Marcela, Grava Cristian

机构信息

Faculty of Electrical Engineering and Information Technology, University of Oradea, 410087 Oradea, Romania.

出版信息

Entropy (Basel). 2024 Aug 23;26(9):720. doi: 10.3390/e26090720.

DOI:10.3390/e26090720
PMID:39330055
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11431465/
Abstract

In this paper, new schemes have been proposed for the estimation of the additive white Gaussian noise (AWGN) channel with intersymbol interference (ISI) in an iterative equalization and decoding system using low-density parity check (LDPC) codes. This article explores the use of the least squares algorithm in various scenarios. For example, the impulse response of the AWGN channel h was initially estimated using a training sequence. Subsequently, the impulse response was calculated based on the training sequence and then re-estimated once using the sequence estimated from the output of the LDPC decoder. Lastly, the impulse response was calculated based on the training sequence and re-estimated twice using the sequence estimated from the output of the LDPC decoder. Comparisons were made between the performances of the three mentioned situations, with the situation in which a perfect estimate of the impulse response of the channel is assumed. The performance analysis focused on how the bit error rate changes in relation to the signal-to-noise ratio. The BER performance comes close to the scenario of having a perfect estimate of the impulse response when the estimation is performed based on the training sequence and then re-estimated twice from the sequence obtained from the output of the LDPC decoder.

摘要

在本文中,针对使用低密度奇偶校验(LDPC)码的迭代均衡和解码系统中存在符号间干扰(ISI)的加性高斯白噪声(AWGN)信道估计问题,提出了新的方案。本文探讨了最小二乘算法在各种场景下的应用。例如,AWGN信道h的冲激响应最初使用训练序列进行估计。随后,根据训练序列计算冲激响应,然后使用从LDPC解码器输出估计的序列再次进行估计。最后,根据训练序列计算冲激响应,并使用从LDPC解码器输出估计的序列进行两次重新估计。对上述三种情况的性能与假设信道冲激响应能完美估计的情况进行了比较。性能分析集中在误码率如何随信噪比变化。当基于训练序列进行估计,然后根据从LDPC解码器输出获得的序列进行两次重新估计时,误码率性能接近具有冲激响应完美估计的情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/3bd0e76c6a4f/entropy-26-00720-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/3bd0e76c6a4f/entropy-26-00720-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/c440e46df59a/entropy-26-00720-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/3d65199982a6/entropy-26-00720-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/c39417252448/entropy-26-00720-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/20ce1733a84b/entropy-26-00720-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/bab455181e9f/entropy-26-00720-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/959f/11431465/9a8fcc1918f0/entropy-26-00720-g006.jpg
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Investigating the Combination of Deep Learning for Channel Estimation and Power Optimization in a Non-Orthogonal Multiple Access System.
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