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On Optimality of Myopic Policy in Multi-Channel Opportunistic Access

机译：多渠道机会访问中近视策略的最优性

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摘要

We consider the channel access problem arising in opportunistic scheduling over fading channels, cognitive radio networks, and server scheduling. The multi-channel communication system consists of N channels. Each channel evolves as a time-nonhomogeneous multi-state Markov process. At each time instant, a user chooses M channels to transmit information, and obtains some reward, i.e., throughput, based on the states of the chosen channels. The objective is to design an access policy, i.e., which channels should be accessed at each time instant, such that the expected accumulated discounted reward is maximised over a finite or infinite horizon. The considered problem can be cast into a restless multi-armed bandit (RMAB) problem, which is PSPACE-hard, with the optimal policy usually intractable due to the exponential computation complexity. Hence, a natural alternative is to consider the easily implementable myopic policy that only maximises the immediate reward but ignores the impact of the current strategy on the future reward. In this paper, we perform an analytical study on the performance of the myopic policy for the considered RMAB problem, and establish a set of closed-form conditions to guarantee the optimality of the myopic policy.
机译：我们考虑在衰落信道上的机会调度，认知无线电网络和服务器调度中出现的信道访问问题。多通道通信系统由N个通道组成。每个通道都作为时间非均匀多状态马尔可夫过程演化。在每个时刻，用户选择M个信道来发送信息，并基于所选择的信道的状态获得一些奖励，即吞吐量。目的是设计一种访问策略，即应在每个时刻访问哪些信道，以使预期的累积折扣奖励在有限或无限的范围内最大化。可以将考虑的问题转换为PSPACE难题的不安多臂匪（RMAB）问题，由于指数计算复杂性，通常难以解决最优策略。因此，自然的选择是考虑易于实施的近视策略，该策略仅最大化即时奖励，而忽略了当前策略对未来奖励的影响。在本文中，我们对考虑的RMAB问题的近视策略的性能进行了分析研究，并建立了一组封闭形式的条件以保证近视策略的最优性。

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  • 来源
    《IEEE Transactions on Communications》 |2017年第2期|677-690|共14页
  • 作者

    Kehao Wang; Lin Chen; Jihong Yu;

  • 作者单位

    Key Laboratory of Fiber Optic Sensing Technology and Information Processing, School of Information Engineering, Wuhan University of Technology, Hubei, China;

    Department of Computer Science, Laboratoire de Recherche en Informatique, University of Paris-Sud XI, Orsay, France;

    Department of Computer Science, Laboratoire de Recherche en Informatique, University of Paris-Sud XI, Orsay, France;

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  • 正文语种 eng
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  • 关键词

    Markov processes; Indexes; Sensors; Optimization; Fans; Communication systems;

    机译：马尔可夫过程;索引;传感器;优化;风扇;通信系统;

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