Fast HARQ over Finite Blocklength Codes: A Technique for Low-Latency Reliable Communication
arXiv:1811.05148 · doi:10.1109/TWC.2018.2878713
Abstract
This paper studies the performance of delay-constrained hybrid automatic repeat request HARQ protocols. Particularly, we propose a fast HARQ protocol where, to increase the end-to-end throughput, some HARQ feedback signals and successive message decodings are omitted. Considering quasi-static channels and a bursty communication model, we derive closed-form expressions for the message decoding probabilities as well as the throughput, the expected delay and the error probability of the HARQ setups. The analysis is based on recent results on the achievable rates of finite-length codes and shows the effect of the codeword length on the system performance. Moreover, we evaluate the effect of various parameters such as imperfect channel estimation and hardware on the system performance. As demonstrated, the proposed fast HARQ protocol reduces the packet transmission delay considerably, compared to state-of-the-art HARQ schemes. For example, with typical message decoding delay profiles and a maximum of 2,...,5 transmission rounds, the proposed fast HARQ protocol can improve the expected delay, compared to standard HARQ, by 27, 42, 52 and 60%, respectively, independently of the code rate/fading model.
References in corpus (6)
- Multiuser MIMO Achievable Rates with Downlink Training and Channel State Feedback
- Finite Block-length Analysis of the Incremental Redundancy HARQ
- A Tight Upper Bound for the Third-Order Asymptotics for Most Discrete Memoryless Channels
- On the Benefits of Partial Channel State Information for Repetition Protocols in Block Fading Channels
- Green Communication via Power-optimized HARQ Protocols
- Modelling Decoding Errors in HARQ
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