Rich-ARQ: From 1-bit Acknowledgment to Rich Neural Coded Feedback
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Abstract (arXiv)
This paper reimagines the foundational feedback mechanism in wireless communication, transforming the prevailing 1-bit binary ACK/NACK with a high-dimensional, information-rich vector to transform passive acknowledgment into an active collaboration. We present Rich-ARQ, a paradigm that introduces neural-coded feedback for collaborative physical-layer channel coding between transmitter and receiver. To realize this vision in practice, we develop a novel asynchronous feedback code that eliminates stalling from feedback delays, adapts dynamically to channel fluctuations, and features a lightweight encoder suitable for on-device deployment. We materialize this concept into the first full-stack, standard-compliant software-defined radio prototype, which decouples AI inference from strict radio timing. Comprehensive over-the-air experiments demonstrate that Rich-ARQ achieves significant SNR gains over conventional 1-bit hybrid ARQ and remarkable latency reduction over prior learning-based feedback codes, moving the promise of intelligent feedback from theory to a practical, high-performance reality for next-generation networks.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 29 references that are in the map. First posted on arXiv 8 Feb 2026.
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6 of 29 references.
References · 6
- 2018Deepcode: Feedback Codes via Deep Learningcited by 42
- 2021Federated Edge Learning with Misaligned Over-The-Air Computationcited by 30
- 2022All you need is feedback: Communication with block attention feedback codescited by 10
- 2022Feedback is Good, Active Feedback is Better: Block Attention Active Feedback Codescited by 4
- 2024LightCode: Light Analytical and Neural Codes for Channels with Feedbackcited by 4
- 2024DEEP-IoT: Downlink-Enhanced Efficient-Power Internet of Thingscited by 2
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- 2024Universal Joint Source-Channel Coding for Modulation-Agnostic Semantic Communication
- 2023Accelerating and Compressing Deep Neural Networks for Massive MIMO CSI Feedback