通过良好的手臂识别机会频谱接入

Zhiyang Wang, Ziyu Ying, Cong Shen
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引用次数: 3

摘要

在这项工作中,我们推广了一种不同的多臂抢匪(MAB)工具,称为臂识别,以选择合适的信道进行机会频谱接入(OSA),具有可靠的准确性,同时满足对延迟,能耗和信道切换的严格限制。注意到寻找最佳信道并不总是最优选择,我们偏离著名的最佳臂识别框架,采用良好臂识别(GAI),这导致信道“足够好”,但在相同精度要求下所需的时间和能量消耗要少得多。在新框架下,鲁棒性问题,如延迟或缺失反馈也进行了研究。对算法的性能进行了分析研究,并通过数值模拟进一步验证了算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OPPORTUNISTIC SPECTRUM ACCESS VIA GOOD ARM IDENTIFICATION
In this work, we promote a different tool of multi-armed bandits (MAB), called arm identification, to choose a suitable channel for Opportunistic Spectrum Access (OSA) with proven accuracy while satisfying stringent constraints on delay, energy consumption, and channel switches. Noting that finding the best channel may not always be the optimal choice, we deviate from the celebrated best arm identification framework and adopt good arm identification (GAI), which results in a channel that is "good enough", but requires much less time and energy consumption under the same accuracy requirement. Robustness issues such as delayed or missing feedback are also studied under the new framework. Performance of the proposed algorithm is studied analytically and further corroborated via numerical simulations.
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