O-DSS：一种用于中频带频谱共享的开放动态频谱共享框架，用于蜂窝-雷达共存
O-DSS: An Open Dynamic Spectrum Sharing Framework for Cellular-Radar Coexistence in Mid-band Frequencies
AI总结：
O-DSS是一种基于机器学习的动态频谱共享框架，通过低开销KPMs雷达检测与频谱图定位，实现中频带蜂窝与雷达的实时共存，有效提升频谱利用效率和系统可靠性。
摘要：
随着中频带频谱需求的增长，需要高效的动态频谱共享（DSS）来确保蜂窝网络与现有雷达系统之间的共存。现有的频谱接入系统（SAS）框架依赖于固定环境感知能力（ESC）传感器，这些传感器存在延迟且缺乏灵活性。本文介绍了O-DSS，一种符合O-RAN标准、由机器学习（ML）驱动的DSS框架，能够实现在中频带频率上实时的蜂窝-雷达共存，适用于船载和快速移动的空中雷达。O-DSS集成了低开销的关键性能指标（KPMs）雷达检测与基于频谱图的定位，以驱动细粒度的RAN控制，包括PRB空闲和雷达感知的MCS适应。作为模块化的xApp部署，O-DSS实现了60~毫秒的检测和700~毫秒的撤离延迟，优于现有基线。在模拟和实测测试平台上评估显示，O-DSS通过在SINR≥-4~dB时实现≥99%的雷达检测率和SINR≥8~dB时实现≥95%的定位召回率，确保了现有系统的保护，同时保持了蜂窝性能。
英文摘要：
The growing demand for mid-band spectrum necessitates efficient Dynamic Spectrum Sharing (DSS) to ensure coexistence between cellular networks and incumbent radar systems. Existing Spectrum Access System (SAS) frameworks rely on fixed Environmental Sensing Capability (ESC) sensors, which are latency-prone and inflexible. This paper introduces O-DSS, an O-RAN-compliant, Machine Learning (ML)-driven DSS framework that enables real-time cellular-radar coexistence in mid-band frequencies with shipborne and fast-moving airborne radars. O-DSS integrates radar detection from low-overhead Key Performance Metrics (KPMs) with spectrogram-based localization to drive fine-grained RAN control, including PRB blanking and radar-aware MCS adaptation. Deployed as a modular xApp, O-DSS achieves 60~ms detection and 700~ms evacuation latencies, outperforming existing baselines. Evaluations across simulations and Over-The-Air (OTA) testbeds show that O-DSS ensures robust incumbent protection while maintaining cellular performance by achieving radar detection of $\geq 99\%$ at SINR $\geq -4$~dB and localization recall of $\geq 95\%$ at SINR $\geq 8$~dB.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
