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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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/158018 |
| _version_ | 1811693025280131072 |
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| author | Teo, Willy Way Yang |
| author2 | Teh Kah Chan |
| author_facet | Teh Kah Chan Teo, Willy Way Yang |
| author_sort | Teo, Willy Way Yang |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T06:45:07Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/158018 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:45:07Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | Engineering::Electrical and electronic engineering Teo, Willy Way Yang Deep learning based channel estimation for OFDM system |
| title | 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_short | Deep learning based channel estimation for OFDM system |
| title_sort | deep learning based channel estimation for ofdm system |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/158018 |
| work_keys_str_mv | AT teowillywayyang deeplearningbasedchannelestimationforofdmsystem |