{
  "abstract": "Integrated sensing and communication (ISAC) enables joint communication and sensing using a shared waveform, but its signal design is challenging due to the inherent trade-off between the two objectives, particularly in the short blocklength regime. This paper proposes an autoencoder (AE)-based framework for ISAC waveform design in noncoherent settings. We derive a modified Cramér-Rao bound for multi-target delay estimation and analyze the maximum-likelihood decoding rule for noncoherent communication under correlated fading. These results reveal structural connections and trade-offs between communication and sensing objectives in waveform design. Based on this analysis, the AE learns waveform representations that jointly optimize both functionalities, with a tunable parameter controlling the trade-off. Simulation results show that the proposed design outperforms conventional schemes in both communication reliability and sensing accuracy, especially under short blocklength and fading conditions.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.33605",
  "author_total": 5,
  "authors": [
    {
      "name": "Muah Kim"
    },
    {
      "name": "Shuangyang Li"
    },
    {
      "name": "Tayyebeh Jahani-Nezhad"
    },
    {
      "name": "Rafael F. Schaefer"
    },
    {
      "name": "Giuseppe Caire"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7r306nsvrft73.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.33605",
  "fulltext_url": null,
  "id": "7r306nsvrft73",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.33605",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.IT"
    ],
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "2202|Radar Systems and Signal Processing"
    ]
  ],
  "openalex": "W7214700933",
  "pdf_url": "https://arxiv.org/pdf/2609.33605",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7r306nsvrft73.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:17Z",
      "native_id": "2609.33605",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.33605"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Short-Length Code Designs for Integrated Sensing and Communications: A Deep Learning Approach",
  "title_text": "Short-Length Code Designs for Integrated Sensing and Communications: A Deep Learning Approach",
  "type": "preprint",
  "updated_at": "2026-11-05T15:20:22Z",
  "url": "https://research.draconitic.com/paper/7r306nsvrft73",
  "venue": "arXiv",
  "versions": []
}