The trade-off between reliability, latency, and energy-efficiency is a central problem in communication systems. Advanced hybrid automated repeat request (HARQ) techniques can reduce the number of retransmissions required for reliable communication, but they have a significant computational cost. On the other hand, 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 required for HARQ schemes from the transmitter to the receiver may provide a way to overcome this trade-off. To achieve this, we propose the Reinforcement-based Adaptive Feedback (RAF) scheme, in which the receiver adaptively learns how much additional redundancy it requires to decode a packet and sends rich feedback (i.e., more than a single bit), requesting the coded retransmission of specific symbols. Simulation results show that the RAF scheme achieves a better trade-off between energy-efficiency, reliability, and latency, compared to existing HARQ solutions and a fixed threshold-based policy. Our RAF scheme can easily adapt to different modulation schemes, and since it relies on the posterior probabilities of the codeword symbols at the decoder, it can generalize to different channel statistics.

翻译：可靠性、延迟与能源效率之间的权衡是通信系统的核心问题。先进的混合自动重传请求（HARQ）技术能够减少可靠通信所需的重复传输次数，但其计算成本较高。另一方面，严格的能量约束主要适用于设备端，而接收其数据包的接入点通常连接电网。因此，将HARQ方案所需的计算复杂度从发射端转移至接收端，可能成为突破这一权衡的途径。为此，我们提出基于强化学习的自适应反馈（RAF）方案：接收端通过自适应学习确定解码数据包所需的额外冗余量，并发送富反馈（即超过单个比特的信息），请求对特定符号进行编码重传。仿真结果表明，与现有HARQ解决方案及固定门限策略相比，RAF方案在能源效率、可靠性与延迟之间实现了更优的权衡。该方案可轻松适配不同调制方式，且由于依赖解码器对码字符号的后验概率，能够泛化至不同信道统计特性。