Link Rate Selection using Constrained Thompson Sampling
Link Rate Selection using Constrained Thompson Sampling
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DOI：
10.1109/infocom.2019.8737610
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发表时间：
2019-04
期刊：
影响因子：
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通讯作者：
Harsh Gupta;A. Eryilmaz;R. Srikant
中科院分区：
文献类型：
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作者：
Harsh Gupta;A. Eryilmaz;R. Srikant
本文研究了信道统计信息未知的时变无线信道中的最优链路速率选择问题。最佳链路速率选择的目的是在每个时隙以最佳速率进行传输，以便最大化无线信道/链路的预期吞吐量或等效地最小化预期遗憾。缺乏有关信道状态或信道统计的信息，需要使用在线/顺序学习算法来确定最佳速率。我们提出了一种算法称为CoTS -约束汤普森采样算法，它改进了当前的最先进的，是快速的，也是一般的意义上说，它可以处理几个不同的约束，在同一个算法的问题。我们还证明了期望后悔的一个渐近下界和一个大概率的大视野上界，这表明后悔的增长与时间的顺序意义上的。我们还提供了数值结果，建立CoTS显着优于目前最先进的算法。
We consider the optimal link rate selection problem in time-varying wireless channels with unknown channel statistics. The aim of optimal link rate selection is to transmit at the optimal rate at each time slot in order to maximize the expected throughput of the wireless channel/link or equivalently minimize the expected regret. Lack of information about channel state or channel statistics necessitates the use of online/sequential learning algorithms to determine the optimal rate. We present an algorithm called CoTS - Constrained Thompson sampling algorithm which improves upon the current state-of-the-art, is fast and is also general in the sense that it can handle several different constraints in the problem with the same algorithm. We also prove an asymptotic lower bound on the expected regret and a high probability large-horizon upper bound on the regret, which show that the regret grows logarithmically with time in an order sense. We also provide numerical results which establish that CoTS significantly outperforms the current state-of-the-art algorithms.