{
  "abstract": "We study a dynamic integrated sensing-and-communication problem in which a multi-antenna transmitter communicates with a receiver while simultaneously tracking a moving target governed by a stable Gauss--Markov model. We formulate the sensing--communication trade-off as a rate--distortion problem, where the communication rate is defined through the Verdú--Han information spectrum and the sensing distortion is measured by the long-run minimum mean square tracking error in angle and distance. We construct a tractable outer region by lower bounding this distortion through the posterior Cramér--Rao bound (PCRB). The control problem is partially observed because the target state is not directly available to the transmitter. We therefore introduce a belief-augmented information state and show, under the stated regularity assumptions, that stationary randomized Markov policies suffice for the covariance-based scalarized problem used in the outer bound. We then derive, under the stated large-block conditions, a Gaussian covariance-control outer bound by showing that, in the large-block regime, the sensing belief transition becomes asymptotically covariance sufficient; consequently, Gaussian signaling with the same stationary covariance policy preserves the stationary PCRB asymptotically while maximizing the communication reward for each transmit covariance. Numerical experiments compare an extended Kalman filter-based achievable frontier with a PCRB-based Gaussian covariance-control outer frontier.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.36143",
  "author_total": 4,
  "authors": [
    {
      "name": "Mohammadreza Bakhshizadeh Mohajer"
    },
    {
      "name": "Luca Barletta"
    },
    {
      "name": "Alex Dytso"
    },
    {
      "name": "Giuseppe Caire"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/beh9ve27ka2jd.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.36143",
  "fulltext_url": null,
  "id": "beh9ve27ka2jd",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.36143",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.IT"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "2202|Radar Systems and Signal Processing"
    ]
  ],
  "openalex": "W7214955660",
  "pdf_url": "https://arxiv.org/pdf/2609.36143",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/beh9ve27ka2jd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:35Z",
      "native_id": "2609.36143",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.36143"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Fundamental Limits of Dynamic Tracking and Communication: A Stationary Policy Formulation",
  "title_text": "Fundamental Limits of Dynamic Tracking and Communication: A Stationary Policy Formulation",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:35Z",
  "url": "https://research.draconitic.com/paper/beh9ve27ka2jd",
  "venue": "arXiv",
  "versions": []
}