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arXiv 1804.02609eess.SYcs.ITcs.SYmath.ITmath.OC
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关于多通信通道的远程估计

On Remote Estimation with Multiple Communication Channels

Coordinated Science Laboratory, University of Illinois at Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校协调科学实验室)

Xiaobin Gao, Emrah Akyol, Tamer Basar

AI总结:

本文研究多通信通道下的远程估计问题,指出传统对称阈值策略在多通道环境下不再最优,并引入辅助通道以确定状态符号,证明阈值-阈值策略在特定条件下最优。

摘要:

本文考虑多通信通道下的顺序传感器调度和远程估计问题。不同于传统单一通信通道的远程估计范式,本文考虑两个具有不同特性的通道(一个便宜但噪声大,另一个昂贵但无噪声)。通过反例表明,传统对称阈值策略在多通道环境下不再最优。为使问题可解,引入辅助通道向接收器指示底层状态符号。在某些技术假设下,证明阈值-阈值通信调度策略最优。通过动态规划分析结果,揭示了一些继承自单通道设置的已知性质,如不耗尽噪声通道的所有机会。

英文摘要:

This paper considers a sequential sensor scheduling and remote estimation problem with multiple communication channels. Departing from the classical remote estimation paradigm, which involves one communication channel (noiseless or noisy), we consider here the more realistic setting of two channels with different characteristics (one is cheap but noisy, the other one is costly but noiseless). We first show, via a counter-example, that the common folklore of applying symmetric threshold-based policy, which is well known to be optimal (for unimodal state densities) in the classical remote estimation problem, can no longer be optimal in our setting. In view of that, and in order to make the problem tractable, we introduce a side channel which signals to the receiver the sign of the underlying state. We show, under some technical assumptions, that a threshold-in-threshold based communication scheduling is optimal. The impact of the results is analyzed numerically based on dynamic programming. This numerical analysis reveals some rather surprising results inheriting known properties from the single channel settings, such as not exhausting all the opportunities available for the noisy channel.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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