Power Allocation of Sensor Transmission for Remote Estimation Over an Unknown Gilbert-Elliott Channel

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Abstract

In this paper, we consider the problem of scheduling the power of a sensor when transmitting over an unknown Gilbert-Elliott (GE) channel for remote state estimation. The sensor supports two power modes, namely low power and high power, which are to be selected for transmission over the channel in order to minimize a cost on the error covariance, while satisfying the energy constraints. The remote estimator provides error-free acknowledgement/negative-acknowledgement (ACK/NACK) messages to the sensor only when low power is utilized. We first consider the Partially Observable Markov Decision Process (POMDP) problem for the case of known GE channels and derive conditions for optimality of a stationary schedule. Next, a Bayesian inference approach is used through which the channels statistics are approximately learned when they are initially unknown. An algorithm is proposed in which the sensor adjusts its scheduling policy based on the energy constraint.

Original languageEnglish
Title of host publicationEuropean Control Conference 2020, ECC 2020
PublisherIEEE
Pages1461-1467
Number of pages7
ISBN (Electronic)9783907144015
Publication statusPublished - May 2020
MoE publication typeA4 Article in a conference publication
EventEuropean Control Conference - ITMO University | Virtual, Saint Petersburg, Russian Federation
Duration: 12 May 202015 May 2020
Conference number: 18
https://ecc20.eu

Conference

ConferenceEuropean Control Conference
Abbreviated titleECC
Country/TerritoryRussian Federation
CitySaint Petersburg
Period12/05/202015/05/2020
Internet address

Keywords

  • Bayesian inference
  • Gilbert-Elliott channel
  • Partially observable Markov decision process
  • Power allocation
  • Remote estimation

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