End-to-End PSK Signals Demodulation Using Convolutional Neural Network
Demodulation techniques are of central importance for achieving intelligent receiving. Improvement in demodulation performance enhances the overall performance of a communication system correspondingly. However, conventional demodulators require dedicated hardware platforms leading to high implement...
| Príomhchruthaitheoirí: | , , |
|---|---|
| Formáid: | Alt |
| Teanga: | English |
| Foilsithe / Cruthaithe: |
IEEE
2022-01-01
|
| Sraith: | IEEE Access |
| Ábhair: | |
| Rochtain ar líne: | https://ieeexplore.ieee.org/document/9775936/ |
| Achoimre: | Demodulation techniques are of central importance for achieving intelligent receiving. Improvement in demodulation performance enhances the overall performance of a communication system correspondingly. However, conventional demodulators require dedicated hardware platforms leading to high implementation costs and time-consuming development. This work proposes a unified architecture for end-to-end automatic demodulated modulated signals. The proposed demodulator utilizes the residual unit and fully convolutional network (R-FCN) to extract the time-domain feature of the modulated signal and determine the transmitted symbols to realize the demodulation of a received signal. Simulations show that the proposed method has better demodulation performance compared to existing methods. It is further demonstrated that when the signal-to-noise ratios (SNR) exceed 2dB, the proposed demodulator exhibits similar demodulation performance to symbol-unsynchronized data compared to conventional demodulators. |
|---|---|
| ISSN: | 2169-3536 |