Problem
Research questions and friction points this paper is trying to address.
Optimizing reliability-latency-energy trade-off in communications.
Reducing computational costs in HARQ techniques.
Shifting complexity from transmitter to receiver.
Learning-Based Rich Feedback HARQ for Energy-Efficient Uplink Short Packet Transmission
🤖 AI Summary
To jointly optimize reliability, latency, and energy efficiency in short-packet uplink transmission, this paper proposes a receiver-driven Adaptive Rich Feedback (RAF) mechanism. Unlike conventional single-bit HARQ feedback, RAF employs reinforcement learning to enable symbol-level retransmission decisions, offloading the computationally intensive feedback generation from resource-constrained user equipment to power-adequate access points. RAF generalizes across modulation schemes and time-varying channel statistics without requiring prior channel state information. Experimental results demonstrate that, compared to classical HARQ, RAF significantly reduces terminal energy consumption (average reduction >40%), improves link reliability (reducing block error rate by 1–2 orders of magnitude), and decreases end-to-end latency—achieving robustness and practicality under diverse channel conditions.
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Reinforcement-based adaptive feedback
Energy-efficient uplink transmission
Adaptive rich HARQ scheme
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