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Quickest Change Point Detection with Measurements over a Lossy Link

Kv, Kv and Chattopadhyay, A and Kumar, A and Sundaresan, R (2023) Quickest Change Point Detection with Measurements over a Lossy Link. In: UNSPECIFIED, pp. 4843-4848.

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Official URL: https://doi.org/10.1109/CDC49753.2023.10384241

Abstract

Motivated by Industry 4.0 applications, we consider quickest change point detection (QCD) when process measurements are transmitted by a sensor over a lossy wireless link to a decision maker (DM). The sensor node samples measurements using a Bernoulli sampling process, and places the measurement samples in a transmit queue of the transmitter. The transmitter uses a retransmit-until-success transmission strategy to deliver packets to the DM over the lossy link, which is modeled as an independent Bernoulli process and has different loss probabilities before and after the change. We pose the QCD problem in the non-Bayesian setting under Lorden's framework 1, and derive a CUSUM algorithm. By defining a suitable Markov process, involving the DM measurements and the queue length process, we show that the problem reduces to QCD of a Markov process. Characterizing the information measure I per measurement sample at the DM, our analysis proves the asymptotic optimality of our algorithm when the false alarm rate tends to zero. We discuss extensions of the analysis to periodic sampling and no-retransmission cases. Through numerical analysis, we demonstrate trade-offs that can be used to optimize system design parameters such as the sampling rate of the measurement process in the non-asymptotic regime. © 2023 IEEE.

Item Type: Conference Paper
Publication: Proceedings of the IEEE Conference on Decision and Control
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 17 May 2024 04:40
Last Modified: 17 May 2024 04:40
URI: https://eprints.iisc.ac.in/id/eprint/84548

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