{
  "abstract": "The cloud radio access network (C-RAN) mitigates inter-cell interference by jointly processing the observations of distributed remote units (RUs) at a centralized unit (CU), but limited fronthaul capacity forces each RU to compress its received signal. Under transform-compress-forward, an RU transforms its signal and quantizes the resulting coefficients, with bit allocation distributing a finite bit budget across them. Classical reverse waterfilling assumes Gaussian sources, yet practical finite-alphabet symbols carry mutual information that saturates at $\\log_2 M$, leaving bit allocation for such inputs unresolved. We address this by formulating bit allocation as maximizing the finite-alphabet generalized mutual information (GMI) achieved after linear MMSE (LMMSE) detection at the CU. Via the I-MMSE relation, this yields a fixed-point update whose converged solution decomposes into a vessel height, a shared water level, and a finite-alphabet mercury level; we term it {reverse mercury/waterfilling} (RMWF). Numerical results show that RMWF sustains end-to-end rate under tight fronthaul budgets and remains robust under antenna scaling, which is increasingly consequential as antenna counts outpace fronthaul capacity in modern C-RAN.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.21265",
  "author_total": 4,
  "authors": [
    {
      "name": "Subin Shin"
    },
    {
      "name": "Jaehoon Lee"
    },
    {
      "name": "Seok-Hwan Park"
    },
    {
      "name": "Jeonghun Park"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/271yy4sfgfh38.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.21265",
  "fulltext_url": null,
  "id": "271yy4sfgfh38",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.21265",
  "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",
      "eess.SP"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "2208|Advanced MIMO Systems Optimization"
    ]
  ],
  "openalex": "W7213881208",
  "pdf_url": "https://arxiv.org/pdf/2609.21265",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/271yy4sfgfh38.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:07Z",
      "native_id": "2609.21265",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.21265"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Fronthaul Compression for Uplink Cloud-RAN with Finite-Alphabet Inputs: A Reverse Mercury/Waterfilling Approach",
  "title_text": "Fronthaul Compression for Uplink Cloud-RAN with Finite-Alphabet Inputs: A Reverse Mercury/Waterfilling Approach",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:07Z",
  "url": "https://research.draconitic.com/paper/271yy4sfgfh38",
  "venue": "arXiv",
  "versions": []
}