Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158018
Title: Deep learning based channel estimation for OFDM system
Authors: Teo, Willy Way Yang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: 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
Project: A3255-211
Abstract: 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.
URI: https://hdl.handle.net/10356/158018
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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