A Joint Data Compression and Time-Delay Estimation Method For Distributed Systems via Extremum Encoding

Fuente: arXiv
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Auteurs principaux: Weiss, Amir, Kochman, Yuval, Wornell, Gregory W.
Format: Preprint
Publié: 2024
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author Weiss, Amir
Kochman, Yuval
Wornell, Gregory W.
author_facet Weiss, Amir
Kochman, Yuval
Wornell, Gregory W.
contents Motivated by the proliferation of mobile devices, we consider a basic form of the ubiquitous problem of time-delay estimation (TDE), but with communication constraints between two non co-located sensors. In this setting, when joint processing of the received signals is not possible, a compression technique that is tailored to TDE is desirable. For our basic TDE formulation, we develop such a joint compression-estimation strategy based on the notion of what we term "extremum encoding", whereby we send the index of the maximum of a finite-length time-series from one sensor to another. Subsequent joint processing of the encoded message with locally observed data gives rise to our proposed time-delay "maximum-index"-based estimator. We derive an exponentially tight upper bound on its error probability, establishing its consistency with respect to the number of transmitted bits. We further validate our analysis via simulations, and comment on potential extensions and generalizations of the basic methodology.
format Preprint
id arxiv_https___arxiv_org_abs_2404_09244
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Joint Data Compression and Time-Delay Estimation Method For Distributed Systems via Extremum Encoding
Weiss, Amir
Kochman, Yuval
Wornell, Gregory W.
Signal Processing
Motivated by the proliferation of mobile devices, we consider a basic form of the ubiquitous problem of time-delay estimation (TDE), but with communication constraints between two non co-located sensors. In this setting, when joint processing of the received signals is not possible, a compression technique that is tailored to TDE is desirable. For our basic TDE formulation, we develop such a joint compression-estimation strategy based on the notion of what we term "extremum encoding", whereby we send the index of the maximum of a finite-length time-series from one sensor to another. Subsequent joint processing of the encoded message with locally observed data gives rise to our proposed time-delay "maximum-index"-based estimator. We derive an exponentially tight upper bound on its error probability, establishing its consistency with respect to the number of transmitted bits. We further validate our analysis via simulations, and comment on potential extensions and generalizations of the basic methodology.
title A Joint Data Compression and Time-Delay Estimation Method For Distributed Systems via Extremum Encoding
topic Signal Processing
url https://arxiv.org/abs/2404.09244