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.

中文翻译：

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远程状态估计中动态多通道分配的惠特尔指数策略

在本文中，我们考虑了多智能体系统远程状态估计的动态信道分配。对于每个子系统，传感器测量其状态并通过丢包通道传输数据，该通道由远程估计器动态分配。我们首先将问题表述为马尔可夫决策过程。鉴于难以获得大规模问题的最优策略，我们基于 Whittle 指数为多臂老虎机 (RMAB) 问题开发了一个次优启发式策略。Whittle 指数策略的性能从理论和实践两个方面进行评估。数值例子说明了惠特尔指数政策的强劲表现。