abdulkarimgizzini/Enhancing_Least_Square_Channel_Estimation_Using_Deep_Learning

This repository includes the source code of the LS-DNN based channel estimators proposed in "Enhancing Least Square Channel Estimation Using Deep Learning" paper that is published in the proceedings of the 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) virtual conference.

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This project helps wireless communications engineers improve the accuracy of channel estimation in OFDM systems. It takes raw communication signals and produces more precise channel estimates by leveraging deep learning techniques alongside traditional least square methods. The primary user would be a researcher or engineer working on signal processing for wireless networks.

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Use this if you are a wireless communications researcher or engineer looking to enhance the performance of OFDM channel estimation using deep learning.

Not ideal if you need a plug-and-play solution for a live production system, as this is research-focused code requiring a deep understanding of the underlying algorithms.

wireless-communication OFDM channel-estimation signal-processing deep-learning-research
No License Stale 6m No Package No Dependents
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Adoption 8 / 25
Maturity 8 / 25
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MATLAB

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Last pushed

Feb 23, 2023

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