Communication System with Walsh Transform-Based End-to-End Autoencoder
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| Publicado en: | Electronics vol. 14, no. 23 (2025), p. 4738-4759 |
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| Autor principal: | |
| Otros Autores: | , |
| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3280947536 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2079-9292 | ||
| 024 | 7 | |a 10.3390/electronics14234738 |2 doi | |
| 035 | |a 3280947536 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231458 |2 nlm | ||
| 100 | 1 | |a Knyva Mindaugas | |
| 245 | 1 | |a Communication System with Walsh Transform-Based End-to-End Autoencoder | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper investigates the design of end-to-end (E2E) autoencoders within AI-enhanced communication systems. It emphasizes the advantages of transitioning from Fast Fourier Transform (FFT)-based Orthogonal Frequency Division Multiplexing (OFDM) to a modulation technique based on the Walsh–Hadamard transform (WHT). This study underscores the WHT’s use of aperiodic basis functions, in contrast with the periodic bases of Fourier transforms. The proposed E2E autoencoder model integrates neural networks in both the transmitter and receiver for signal processing. The model is trained to adapt the bit rate according to the measured channel signal-to-noise ratio (SNR) using the same neural network, enabling operation at low SNR levels (down to −10 dB). Additionally, the model was experimentally validated in a laboratory setting using a software-defined radio (SDR)-based system setup. | |
| 653 | |a Wireless communications | ||
| 653 | |a Receivers & amplifiers | ||
| 653 | |a Machine learning | ||
| 653 | |a Simulation | ||
| 653 | |a Deep learning | ||
| 653 | |a Signal processing | ||
| 653 | |a Neural networks | ||
| 653 | |a Fourier transforms | ||
| 653 | |a Walsh transforms | ||
| 653 | |a Fast Fourier transformations | ||
| 653 | |a Systems design | ||
| 653 | |a Adaptation | ||
| 653 | |a Basis functions | ||
| 653 | |a Design | ||
| 653 | |a Communications systems | ||
| 653 | |a Orthogonal Frequency Division Multiplexing | ||
| 653 | |a Software radio | ||
| 653 | |a Signal to noise ratio | ||
| 700 | 1 | |a Ruseckas Julius | |
| 700 | 1 | |a Alfonsas, Juršėnas | |
| 773 | 0 | |t Electronics |g vol. 14, no. 23 (2025), p. 4738-4759 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3280947536/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3280947536/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3280947536/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |