Learning-Based Rich Feedback HARQ for Energy-Efficient Uplink Short Packet Transmission
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866929716176355328 |
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| author | Vejling, Martin Voigt Chiariotti, Federico Kalør, Anders Ellersgaard Gündüz, Deniz Liva, Gianluigi Popovski, Petar |
| author_facet | Vejling, Martin Voigt Chiariotti, Federico Kalør, Anders Ellersgaard Gündüz, Deniz Liva, Gianluigi Popovski, Petar |
| contents | The trade-off between reliability, latency, and energy efficiency is a central problem in communication systems. Advanced hybrid automated repeat request (HARQ) techniques reduce retransmissions required for reliable communication but incur high computational costs. Strict energy constraints apply mainly to devices, while the access point receiving their packets is usually connected to the electrical grid. Therefore, moving the computational complexity from the transmitter to the receiver may provide a way to improve this trade-off. We propose the reinforcement-based adaptive feedback (RAF) scheme, a departure from traditional single-bit feedback HARQ, introducing adaptive rich feedback where the receiver requests the coded retransmission of specific symbols. Simulation results show that RAF achieves a better trade-off between energy efficiency, reliability, and latency, compared to existing HARQ solutions. Our RAF scheme can easily adapt to different modulation schemes and can also generalize to different channel statistics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_02726 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Learning-Based Rich Feedback HARQ for Energy-Efficient Uplink Short Packet Transmission Vejling, Martin Voigt Chiariotti, Federico Kalør, Anders Ellersgaard Gündüz, Deniz Liva, Gianluigi Popovski, Petar Information Theory Signal Processing The trade-off between reliability, latency, and energy efficiency is a central problem in communication systems. Advanced hybrid automated repeat request (HARQ) techniques reduce retransmissions required for reliable communication but incur high computational costs. Strict energy constraints apply mainly to devices, while the access point receiving their packets is usually connected to the electrical grid. Therefore, moving the computational complexity from the transmitter to the receiver may provide a way to improve this trade-off. We propose the reinforcement-based adaptive feedback (RAF) scheme, a departure from traditional single-bit feedback HARQ, introducing adaptive rich feedback where the receiver requests the coded retransmission of specific symbols. Simulation results show that RAF achieves a better trade-off between energy efficiency, reliability, and latency, compared to existing HARQ solutions. Our RAF scheme can easily adapt to different modulation schemes and can also generalize to different channel statistics. |
| title | Learning-Based Rich Feedback HARQ for Energy-Efficient Uplink Short Packet Transmission |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2306.02726 |