Application of deep-learning based approach for OFDM system
In comparison to other modulation techniques, Orthogonal frequency-division multiplexing (OFDM) techniques are widely used for wireless communications. It has high spectral efficiency, is immune to impulse interference, and can handle very strong echoes. However, channel estimation and signal detect...
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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/10356/158302 |
| _version_ | 1826114090512154624 |
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| author | Zhang, Yutong |
| author2 | Teh Kah Chan |
| author_facet | Teh Kah Chan Zhang, Yutong |
| author_sort | Zhang, Yutong |
| collection | NTU |
| description | In comparison to other modulation techniques, Orthogonal frequency-division multiplexing (OFDM) techniques are widely used for wireless communications. It has high spectral efficiency, is immune to impulse interference, and can handle very strong echoes. However, channel estimation and signal detection are difficult for OFDM system without cyclic prefix. Therefore, the aim of this report is to design an AI receiver to estimate channels and detect channels of OFDM system. The accuracy of the model will be tested by comparing the Bit-error rate (BER) of simulation results. The network model was built by using python. |
| first_indexed | 2024-10-01T03:33:30Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/158302 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:33:30Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1583022023-07-07T18:57:31Z Application of deep-learning based approach for OFDM system Zhang, Yutong Teh Kah Chan School of Electrical and Electronic Engineering EKCTeh@ntu.edu.sg Engineering::Electrical and electronic engineering::Wireless communication systems In comparison to other modulation techniques, Orthogonal frequency-division multiplexing (OFDM) techniques are widely used for wireless communications. It has high spectral efficiency, is immune to impulse interference, and can handle very strong echoes. However, channel estimation and signal detection are difficult for OFDM system without cyclic prefix. Therefore, the aim of this report is to design an AI receiver to estimate channels and detect channels of OFDM system. The accuracy of the model will be tested by comparing the Bit-error rate (BER) of simulation results. The network model was built by using python. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-31T07:04:50Z 2022-05-31T07:04:50Z 2022 Final Year Project (FYP) Zhang, Y. (2022). Application of deep-learning based approach for OFDM system. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158302 https://hdl.handle.net/10356/158302 en A3258-211 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering::Wireless communication systems Zhang, Yutong Application of deep-learning based approach for OFDM system |
| title | Application of deep-learning based approach for OFDM system |
| title_full | Application of deep-learning based approach for OFDM system |
| title_fullStr | Application of deep-learning based approach for OFDM system |
| title_full_unstemmed | Application of deep-learning based approach for OFDM system |
| title_short | Application of deep-learning based approach for OFDM system |
| title_sort | application of deep learning based approach for ofdm system |
| topic | Engineering::Electrical and electronic engineering::Wireless communication systems |
| url | https://hdl.handle.net/10356/158302 |
| work_keys_str_mv | AT zhangyutong applicationofdeeplearningbasedapproachforofdmsystem |