{
  "abstract": "High-resolution remote sensing imagery (RSI) transmission is constrained by satellite-ground bandwidth and channel impairments, yet existing methods struggle to simultaneously achieve extreme compression and robust transmission. To address this, we propose a dual-branch vector-quantization aided satellite digital semantic communication (DVQ-SDSC) framework for RSI transmission over affine frequency division multiplexing (AFDM), whose bandwidth savings arise from two interrelated aspects. First, at the source-coding level, a dual-branch framework is developed to unify deep joint semantic coding, VQ-aided index transmission, channel estimation and adaption in an end-to-end architecture; departing from symmetric encoder designs, the codec is recast as an asymmetric dual-branch architecture that separately processes the high-frequency residuals and the low-frequency structural semantics, with gated fusion and channel-adaptive reconstruction jointly restoring the semantic content. Second, at the index-coding level, we develop a principal component analysis (PCA)-aided codebook reordering to align index topology with latent correlations, and devise group differential pulse-code modulation (G-DPCM) to encode prediction residuals rather than absolute indices, lowering the index bitrate while locally isolating clipping and channel errors. A two-stage training strategy further decouples channel impairments from the semantic codec. FAIR1M experiments over 3GPP NTN-TDL-D demonstrate that DVQ-SDSC with G-DPCM index coding outperforms the conventional JPEG-LDPC scheme at the base rate of 0.0625 bits per pixel (BPP), and that G-DPCM applies directly to the trained codec without retraining, yielding additional index compression at no extra cost.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.35906",
  "author_total": 10,
  "authors": [
    {
      "name": "Jianqiao Chen"
    },
    {
      "name": "Nan Ma"
    },
    {
      "name": "Xiaodong Xu"
    },
    {
      "name": "Tingting Zhu"
    },
    {
      "name": "Huishi Song"
    },
    {
      "name": "Chen Dong"
    },
    {
      "name": "Rui Meng"
    },
    {
      "name": "Wenkai Liu"
    },
    {
      "name": "Ke Peng"
    },
    {
      "name": "Ping Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6rejw6pcyrmy0.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.35906",
  "fulltext_url": null,
  "id": "6rejw6pcyrmy0",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.35906",
  "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",
      "math.IT"
    ],
    [
      "openalex",
      "1707|Advanced Data Compression Techniques"
    ]
  ],
  "openalex": "W7214913006",
  "pdf_url": "https://arxiv.org/pdf/2609.35906",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6rejw6pcyrmy0.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:35Z",
      "native_id": "2609.35906",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.35906"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Dual-Branch Vector-Quantization-Aided Satellite Digital Semantic Communication with Index Compression for High-Resolution RSI Over AFDM",
  "title_text": "Dual-Branch Vector-Quantization-Aided Satellite Digital Semantic Communication with Index Compression for High-Resolution RSI Over AFDM",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:35Z",
  "url": "https://research.draconitic.com/paper/6rejw6pcyrmy0",
  "venue": "arXiv",
  "versions": []
}