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Whittle Index Policy for Dynamic Multichannel Allocation in Remote State Estimation

机译:远程状态估计中动态多通道分配的削减指数策略

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摘要

In this paper, we consider dynamic channel allocation for remote state estimation of multiagent systems. For each subsystem, a sensor measures its state and transmits the data via a packet-dropping channel, which is dynamically allocated by the remote estimator. We first formulate the problem as a Markov decision process. Given the difficulty of obtaining an optimal policy of large-scale problems, we develop a suboptimal heuristic policy based on the Whittle index for the restless multiarmed bandit (RMAB) problem. The performance of the Whittle index policy is evaluated from both theoretical and practical aspects. The strong performance of Whittle index policy is illustrated by the numerical examples.
机译:在本文中,我们考虑用于远程状态估计的多态系统的动态信道分配。对于每个子系统,传感器测量其状态并经由分组丢弃信道发送数据,该信道由远程估计器动态分配。我们首先向马尔可夫决策过程制定问题。鉴于获得大规模问题的最佳政策的难度,我们基于焦躁的多星座(RMAB)问题的薄片指数来发展次优的启发式政策。从理论和实践方面评估了削减指数政策的表现。数值例子说明了削弱指数政策的强大性能。

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