{
  "abstract": "This paper focuses on robust beamforming for orthogonal time frequency space (OTFS)-enabled massive multiple-input multiple-output (MIMO) systems under channel state information (CSI) uncertainty. In high-mobility satellite communications, uncertain CSI severely degrades beamforming accuracy and poses a major challenge to meeting users' quality of service (QoS) requirements. To address this challenge, we first formulate a chance-constrained optimization problem aiming to minimize the total transmit power while guaranteeing a predefined outage probability. Building on a 3D delay-Doppler-angle (DDA) channel representation, we propose a data-driven approach using support vector clustering (SVC) to model the uncertain CSI as an asymmetric uncertainty set. We then derive a robust counterpart that reformulates the intractable chance constraints into a deterministic semidefinite program. Finally, we design a graphics processing unit (GPU)-accelerated parallelizable alternating direction method of multipliers (ADMM) algorithm to address the computational complexity of large-scale antenna arrays. Simulation results show that the proposed SVC-based design reduces transmit power compared with conventional beamforming schemes, and that the GPU-accelerated ADMM achieves a speedup. These results confirm that the proposed framework achieves improved robustness, energy efficiency, and efficient computation in dynamic massive MIMO networks.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.34763",
  "author_total": 2,
  "authors": [
    {
      "name": "Haonan Zhang"
    },
    {
      "name": "Weihua Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5bp78bsj3hk5r.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.34763",
  "fulltext_url": null,
  "id": "5bp78bsj3hk5r",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.34763",
  "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",
      "2208|Advanced MIMO Systems Optimization"
    ]
  ],
  "openalex": "W7214748389",
  "pdf_url": "https://arxiv.org/pdf/2609.34763",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5bp78bsj3hk5r.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:17Z",
      "native_id": "2609.34763",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.34763"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "GPU-Accelerated Robust Beamforming for OTFS Massive MIMO with CSI Uncertainty",
  "title_text": "GPU-Accelerated Robust Beamforming for OTFS Massive MIMO with CSI Uncertainty",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:17Z",
  "url": "https://research.draconitic.com/paper/5bp78bsj3hk5r",
  "venue": "arXiv",
  "versions": []
}