针对具有不可靠反馈的速率自适应HARQ的优化非对称反馈检测
Optimized Asymmetric Feedback Detection for Rate-adaptive HARQ with Unreliable Feedback
AI总结：
本文针对不可靠反馈信道下的IR-HARQ，提出非对称反馈检测方案保护NACK，并将其建模为MDP以自适应调整传输速率，从而在中断概率约束下提升吞吐量。
摘要：
本文研究在不可靠反馈信道上的下行链路增量冗余混合自动重传请求（IR-HARQ）。由于肯定反馈（即ACK）错误的影响小于否定反馈（即NACK）错误的影响，提出了一种非对称反馈检测方案来保护NACK并进一步降低中断概率。我们将HARQ过程建模为马尔可夫决策过程（MDP）模型，以在无需增强反馈和额外反馈开销的情况下适应每次传输尝试的传输速率。我们旨在通过寻找最优非对称检测阈值，在特定中断概率要求下优化HARQ过程的性能。在下行链路瑞利衰落信道和5G新空口（NR）PUCCH反馈信道上获得的数值结果表明，通过应用非对称反馈检测和自适应速率分配，可以在中断概率限制下实现更高的吞吐量。
英文摘要：
This work considers downlink incremental redundancy Hybrid Automatic Repeat Request (IR-HARQ) over unreliable feedback channels. Since the impact of positive feedback (i.e., ACK) error is smaller than that of negative feedback (i.e., NACK) error, an asymmetric feedback detection scheme is proposed to protect NACK and further reduce the outage probability. We formulate the HARQ process as a Markov Decision Process (MDP) model to adapt to the transmission rate of each transmission attempt without enriched feedback and additional feedback cost. We aim to optimize the performance of HARQ process under certain outage probability requirements by finding optimal asymmetric detection thresholds. Numerical results obtained on the downlink Rayleigh fading channel and 5G new radio (NR) PUCCH feedback channel show that by applying asymmetric feedback detection and adaptive rate allocation, higher throughput can be achieved under outage probability limitations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
