发表机构
Nokia Bell Labs; Duke University（诺基亚贝尔实验室; 杜克大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究增量冗余中传统反馈机制的问题，提出两种增强反馈和调度机制，一种利用信道统计学习映射得可靠性下限，另一种基于首次传输可靠性信息做决策，两种机制都能提高解码成功率，节省资源。
AI 中文摘要
增量冗余（IR）可通过在多次传输尝试中分散编码比特来降低错误率。然而，传统的带粗略反馈的停等操作常常过度安排重传，触发不必要的解码尝试并增加端到端延迟。本文开发了增强反馈和调度机制，可预测成功解码所需的额外冗余并仅分配所需资源。研究了两种互补策略。一是利用信道统计信息，从信道质量到最小冗余预算学习单次或两次映射，得出混合自动重传请求（HARQ）系统错误概率的可实现可靠性下限。数值结果表明通过适当选择第二次传输冗余可接近该下限，重传大小节省高达60%；二是提出一种基于实现感知的早期反馈机制，利用首次传输可靠性信息在解码前对每个码字做决策。链路级仿真表明两种预测器都具有高精度（约96%），最多在两次传输内增加成功解码概率。
英文摘要
Incremental redundancy (IR) can reduce error rates by spreading coded bits across multiple transmission attempts. However, conventional stop-and-wait operation with coarse feedback often over-provisions retransmissions, triggers unnecessary decoding attempts, and increases end-to-end latency. This paper develops enhanced feedback and scheduling mechanisms that predict the additional redundancy needed for successful decoding and allocate only the required resources. We study two complementary strategies. First, using channel statistics, we learn a one- or two-shot mapping from channel quality to the minimum redundancy budget. As a byproduct, we derive an achievable reliability lower bound on the error probability of hybrid automatic repeat request (HARQ) systems. Numerical results with polar-coded IR-HARQ scheme show that the bound can be closely approached by appropriately selecting the second-transmission redundancy over a wide SNR range with savings up to 60\% in retransmission size. Second, we propose a realization-aware early-feedback mechanism that uses first-transmission reliability information to make per-codeword decisions before decoding: whether the codeword is already decodable, if not, how many additional redundancy versions are needed, or whether decoding is unlikely and rate adaptation is preferable. Link-level simulations with 5G NR LDPC codes show that both predictors achieve high accuracy (about 96\% in our study), increasing the probability of successful decoding within at most two transmission occasions.
Comments6 pages, 6 figures, to be presented at the 62nd Allerton Conference on Communication, Control, and Computing, 2026. September 16 - 18, 2026 Camera-ready version with a few typos corrected
