Deep learning based channel estimation for OFDM system

In this project, we aim to study and design a deep learning based receiver for orthogonal frequency-division multiplexing (OFDM) system. OFDM has been widely adopted in wireless broadband communications to combat frequency-selective fading in wireless channels. In this project, we take advantage of...

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Main Author: Teo, Willy Way Yang
Other Authors: Teh Kah Chan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158018
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1580182023-07-07T19:16:17Z Deep learning based channel estimation for OFDM system Teo, Willy Way Yang Teh Kah Chan School of Electrical and Electronic Engineering EKCTeh@ntu.edu.sg Engineering::Electrical and electronic engineering In this project, we aim to study and design a deep learning based receiver for orthogonal frequency-division multiplexing (OFDM) system. OFDM has been widely adopted in wireless broadband communications to combat frequency-selective fading in wireless channels. In this project, we take advantage of deep learning in handling wireless OFDM channels in an end-to-end approach. We will explore the advantage of the deep learning model to recover the distorted signal. Moreover, the channel state information will not be required as compared with the traditional method. MATLAB simulation will be studied in this project to generate the dataset, and Python programming will be used to train the deep learning neural network. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-26T23:47:30Z 2022-05-26T23:47:30Z 2022 Final Year Project (FYP) Teo, W. W. Y. (2022). Deep learning based channel estimation for OFDM system. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158018 https://hdl.handle.net/10356/158018 en A3255-211 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Teo, Willy Way Yang
Deep learning based channel estimation for OFDM system
description In this project, we aim to study and design a deep learning based receiver for orthogonal frequency-division multiplexing (OFDM) system. OFDM has been widely adopted in wireless broadband communications to combat frequency-selective fading in wireless channels. In this project, we take advantage of deep learning in handling wireless OFDM channels in an end-to-end approach. We will explore the advantage of the deep learning model to recover the distorted signal. Moreover, the channel state information will not be required as compared with the traditional method. MATLAB simulation will be studied in this project to generate the dataset, and Python programming will be used to train the deep learning neural network.
author2 Teh Kah Chan
author_facet Teh Kah Chan
Teo, Willy Way Yang
format Final Year Project
author Teo, Willy Way Yang
author_sort Teo, Willy Way Yang
title Deep learning based channel estimation for OFDM system
title_short Deep learning based channel estimation for OFDM system
title_full Deep learning based channel estimation for OFDM system
title_fullStr Deep learning based channel estimation for OFDM system
title_full_unstemmed Deep learning based channel estimation for OFDM system
title_sort deep learning based channel estimation for ofdm system
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/158018
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