发表机构
Aalborg University; University of Novi Sad（奥尔堡大学; 诺维萨德大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对大规模物联网，提出统一端到端框架，联合建模上行FBL随机接入、感知辅助卫星回程及广播下行，通过随机几何表征可靠性，数值揭示最优接入概率并证明感知余量提升鲁棒性。
AI 中文摘要
大规模物联网（IoT）网络以短数据包运行，其可靠性受到有限块长度（FBL）效应的限制，而远程部署日益依赖低地球轨道（LEO）卫星进行回程连接，这种连接对大气衰减敏感。在本文中，我们提出了一种统一的端到端框架，用于卫星辅助的大规模物联网网络，该框架联合建模了上行链路FBL随机接入、感知辅助卫星回程以及最差用户广播下行链路传输。上行链路可靠性使用随机几何进行表征，而大气感知和保守的信噪比（SNR）余量实现了FBL安全的回程自适应。数值结果揭示了由于空间复用与FBL可靠性之间的权衡而存在的最优上行链路接入概率，并表明感知辅助回程余量显著提高了针对衰减不确定性的鲁棒性。
英文摘要
Massive Internet of Things (IoT) networks operate with short packets whose reliability is limited by finite block- length (FBL) effects, while remote deployments increasingly rely on Low Earth Orbit (LEO) satellites for backhaul connectivity that is sensitive to atmospheric attenuation. In this paper, we pro- pose a unified end-to-end framework for satellite-assisted massive IoT networks that jointly models uplink FBL random access, sensing assisted satellite backhaul, and worst user broadcast downlink transmission. Uplink reliability is characterized using stochastic geometry, while atmospheric sensing and conservative SNR margins enable FBL-safe backhaul adaptation. Numerical results reveal an optimal uplink access probability due to the tradeoff between spatial reuse and FBL reliability, and show that sensing assisted backhaul margins significantly improve robustness against attenuation uncertainty.
DOI：10.1109/ICCWorkshops63917.2026.11586459
