用神经编码反馈取代1比特确认，实现收发端协同通信
Rich-ARQ: From 1-bit Acknowledgment to Rich Neural Coded Feedback
- 用高维向量替代传统1比特确认，实现智能反馈
- 实测信噪比提升显著，延迟降低超过已有学习型方案
- 支持设备端轻量部署，适配下一代无线网络
本文重新构想无线通信的基础反馈机制，将传统的1比特二进制确认（ACK/NACK）升级为高维、信息丰富的向量，使被动确认变为主动协作。提出Rich-ARQ新范式，引入神经编码反馈，在收发端间实现物理层协同编码。为落地此理念，设计新型异步反馈码，消除反馈延迟导致的停滞，动态适应信道变化，且编码器轻量化，适合设备端部署。构建首个全栈、符合标准的软件定义无线电原型，将AI推理与严格射频时序解耦。大量实测验证表明，Rich-ARQ在实际无线环境中相比传统1比特混合式ARQ实现显著的信噪比增益，同时在延迟上大幅优于先前基于学习的反馈方案，使智能反馈从理论走向实用高性能的下一代网络现实。
原文摘要 · Abstract (English)
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.
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