发表机构
North Carolina State University（北卡罗来纳州立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对城市5G网络中强干扰导致RSRP高估无人机连接性的问题，提出轨迹感知系统级框架，联合评估RSRP、RSRQ和SINR，揭示覆盖与可服务性差距，并建议采用多KPM规划。
AI 中文摘要
参考信号接收功率（RSRP）通常用于评估5G蜂窝覆盖，但在强小区间干扰（ICI）下，它可能大幅高估蜂窝连接无人机（UAV）可用的连接性。随着无人机攀升，遮挡减少可能增强服务信号，而对相邻扇区的视距可见性增加可能加剧ICI。本文开发了一个基于3GPP的轨迹感知系统级框架，用于评估城市5G新无线电网络中三维飞行期间无人机的无线电可服务性。该框架在19个站点、57个扇区的部署中联合评估RSRP、参考信号接收质量（RSRQ）和信号与干扰加噪声比（SINR）。我们引入了覆盖-可服务性差距的概念，以量化RSRP可用性与联合服务可用性之间的差异。在RSRP为-100 dBm、RSRQ为-20 dB、SINR为0 dB的评估阈值下，站间距离（ISD）为500 m时提供99.9%的RSRP可用性，但联合服务可用性仅为13.6%，差距达86.3个百分点。将ISD增加到1000 m可将平均SINR和联合可用性从13.6%提高到18.4%，而SINR仍是主要约束。在三次独立模拟实现上平均的结果表明，基于RSRP的空中覆盖不一定转化为任务级无线电可服务性，这促使采用轨迹感知的多关键性能指标（KPM）空中无线电规划。
英文摘要
Reference signal received power (RSRP) is commonly used to assess 5G cellular coverage, but it may substantially overestimate the connectivity available to cellular-connected unmanned aerial vehicles (UAVs) under strong inter-cell interference (ICI). As a UAV ascends, reduced blockage can strengthen the serving signal, while increased line-of-sight visibility to neighboring sectors can intensify ICI. This paper develops a trajectory-aware, 3GPP-based system-level framework for evaluating UAV radio serviceability during a three-dimensional flight in an urban 5G New Radio network. The framework jointly evaluates RSRP, reference signal received quality (RSRQ), and signal-to-interference-plus-noise ratio (SINR) in a 19-site, 57-sector deployment. We introduce the concept of coverage-serviceability gap to quantify the difference between RSRP availability and joint service availability. Under RSRP, RSRQ, and SINR thresholds of -100 dBm, -18 dB, and 0 dB, respectively, an inter-site distance (ISD) of 500 m provides 99.9% RSRP availability but only 13.6% joint service availability, yielding a coverage-serviceability gap of 86.3 percentage points. With RSRQ and SINR thresholds of -22 dB and -6 dB, respectively, joint availability increases to 55.0% and 63.1% for ISDs of 500 m and 1000 m, respectively. These results demonstrate that RSRP-based coverage substantially overestimates joint UAV serviceability under both evaluation configurations, with SINR remaining the limiting metric.
Comments6 pages, 4 figures
