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...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/158302 |
| Summary: | 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. |
|---|