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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Bibliographic Details
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
Description
Summary: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.