English

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

Signal Processing 2024-12-05 v2

Abstract

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.

Keywords

Cite

@article{arxiv.2404.09244,
  title  = {A Joint Data Compression and Time-Delay Estimation Method For Distributed Systems via Extremum Encoding},
  author = {Amir Weiss and Yuval Kochman and Gregory W. Wornell},
  journal= {arXiv preprint arXiv:2404.09244},
  year   = {2024}
}

Comments

Corrected version of our ICASSP'24 paper: Corrected proof of Theorem 1 and corrected caption of figure 2

R2 v1 2026-06-28T15:53:44.096Z