{
  "abstract": "Low-complexity channel state information acquisition is crucial for extremely large-scale multiple-input multiple-output (XL-MIMO) systems. However, practical deployments of non-square uniform planar arrays (UPAs) in hybrid-field environments face prohibitive computational complexity and degraded estimation accuracy due to limited elevation angle-of-arrival (AoA) resolution and deteriorated channel sparsity. To tackle these challenges, we propose a low-complexity channel estimation framework. First, an antenna-domain extrapolation scheme synthesizes a virtually enlarged vertical aperture via the spatial correlation among adjacent elements, breaking the elevation resolution limit. The framework then disentangles the parameter coupling by transforming the two-dimensional joint search into two sequential one-dimensional searches. Specifically, elevation AoAs are extracted via an extrapolation-enhanced discrete Fourier transform-Newtonized orthogonal matching pursuit (NOMP) algorithm along the virtually enlarged vertical uniform linear array (ULA), while azimuth AoAs, ranges, and gains are acquired utilizing a discrete fractional Fourier transform-NOMP algorithm along a horizontal ULA. A subspace fitting-driven path matching algorithm pairs these decoupled parameters. To overcome the accuracy bottleneck of the antenna-domain scheme, a correlation-domain extrapolation scheme is further developed by exploiting the structural properties of the spatial correlation matrix to decouple the near-field quadratic and azimuth phase components, yielding a noise-suppressed virtual array. Numerical results validate the effectiveness of the proposed framework.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2607.18744",
  "author_total": 6,
  "authors": [
    {
      "name": "Yilong Liu"
    },
    {
      "name": "Xi Yang"
    },
    {
      "name": "Binggui Zhou"
    },
    {
      "name": "Yu Han"
    },
    {
      "name": "Ting Liu"
    },
    {
      "name": "Shaodan Ma"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/41aj2rx6bt97y.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2607.18744",
  "fulltext_url": null,
  "id": "41aj2rx6bt97y",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2607.18744",
  "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",
      "eess.SP"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "2208|Millimeter-Wave Propagation and Modeling"
    ]
  ],
  "openalex": "W7170088996",
  "pdf_url": "https://arxiv.org/pdf/2607.18744",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/41aj2rx6bt97y.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:35Z",
      "native_id": "2607.18744",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2607.18744"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Low-Complexity Channel Estimation Framework for Non-Square UPA-Assisted XL-MIMO Systems",
  "title_text": "Low-Complexity Channel Estimation Framework for Non-Square UPA-Assisted XL-MIMO Systems",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:35Z",
  "url": "https://research.draconitic.com/paper/41aj2rx6bt97y",
  "venue": "arXiv",
  "versions": []
}