{
  "id": 16132,
  "url": "https://arxiv.org/abs/2608.00855v1",
  "title": "Partially-Observable Transmission Control for UAV-Enabled Federated Learning in IoT Networks",
  "summary": "Uncrewed aerial vehicle (UAV)-enabled federated learning (FL) can provide flexible, on-demand edge intelligence for large-scale IoT deployments, but operating in shared unlicensed bands makes uplink update delivery interference-coupled and unreliable. In this paper, we develop a packet-level transmission framework that captures buffer overflow, delay violations, and transmission errors, and uses the resulting packet delivery ratio (PDR) to represent partial-update reception through a packetized,",
  "authors": "Masoud Ghazikor, Zhou Ni, Morteza Hashemi",
  "category": "research",
  "topics": null,
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-01T20:28:08.000Z",
  "fetched_at": "2026-08-04T05:10:21.797Z",
  "source_slug": "x-arxiv-fairness-query",
  "source_name": "arXiv fairness query",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/16132",
  "original_url": "https://arxiv.org/abs/2608.00855v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}