Optimization of ARQ Distribution for HARQ Strategies in Delay-Bounded Networks

Jaya Goel, J. Harshan
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引用次数: 1

Abstract

Inspired by several delay-bounded mission-critical applications, optimizing the end-to-end reliability of multi-hop networks is an important problem subject to end-to-end delay constraints on the packets. Towards that direction, Automatic Repeat Request (ARQ) based strategies have been recently proposed wherein the problem statement is to distribute a certain total number of ARQs (that capture end-to-end delay) across the nodes such that the end-to-end reliability is optimized. Although such strategies provide a fine control to trade end-to-end delay with end-to-end reliability, their performance degrades in slowly-varying channel conditions. Pointing at this drawback, in this work, we propose a Chase Combing Hybrid ARQ (CC-HARQ) based multi-hop network addressing a similar problem statement of how to distribute a certain total number of ARQs such that the end-to-end reliability is optimized. Towards solving the problem, first, we identify that the objective function of the optimization problem is intractable due to the presence of Marcum-Q functions in it. As a result, we propose an approximation on the objective function and then prove a set of necessary and sufficient conditions on the near-optimal ARQ distribution. Subsequently, we propose a low-complexity algorithm to solve the problem for any network size. We show that CC-HARQ based strategies are particularly appealing in slow-fading channels wherein the existing ARQ strategies fail.
延迟有界网络中HARQ策略的ARQ分布优化
受一些延迟限制的关键任务应用的启发,优化多跳网络的端到端可靠性是一个受端到端数据包延迟约束的重要问题。在这个方向上,最近提出了基于自动重复请求(ARQ)的策略,其中的问题陈述是在节点之间分配一定总数的ARQ(捕获端到端延迟),从而优化端到端可靠性。尽管这种策略提供了端到端延迟和端到端可靠性之间的良好控制,但它们的性能在缓慢变化的信道条件下会下降。针对这一缺点,在本工作中,我们提出了一种基于Chase梳理混合ARQ (CC-HARQ)的多跳网络,解决了如何分配一定数量的ARQ以优化端到端可靠性的类似问题。为了解决这个问题,首先,我们确定了优化问题的目标函数是难以处理的,因为其中存在Marcum-Q函数。因此,我们提出了目标函数的近似,并证明了近似最优ARQ分布的一组充分必要条件。随后,我们提出了一种低复杂度的算法来解决任何网络规模的问题。我们表明,基于CC-HARQ的策略在现有ARQ策略失败的慢衰落信道中特别有吸引力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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