Dynamic Spectrum Sharing (DSS) enables flexible activation of additional spectrum resources but leaves open a key runtime question: once new spectrum becomes available, which steering mechanism should migrate connected devices toward it with minimum service disruption? We present the first PHY-aware characterization of 3GPP-compliant UE steering mechanisms, including Bandwidth Part (BWP) reconfiguration, Carrier Aggregation (CA), E-UTRA-NR Dual Connectivity (EN-DC), Connected-Mode Handover (HO), and Release and Redirection (R&R), using modem-level traces from devices connected to operational networks, collected across 1,600 executions over four months in 12 urban areas. By mapping each mechanism to observable PHY-layer milestones, we decompose steering latency into intrinsic PHY-centric execution and RRC-to-PHY completion components, revealing substantial heterogeneity: NR BWP achieves 6.25 ms mean latency with zero tail exceedance above 50 ms, while CA exceeds 1225 ms; mobility procedures remain largely modem-bound, whereas discovery-driven mechanisms experience significant RRC-to-PHY completion amplification. Guided by these measurements, we design POLARIS, an O-RAN-based system that selects the least disruptive steering mechanism via a two-parameter disruption score. POLARIS reduces mean latency by up to 85.1% and T95 by 89.7% over static or non-adaptive baselines, eliminates tail exceedance above 50 ms, and avoids high-disruption mechanisms, demonstrating that PHY-layer execution profiling enables reliable and context-aware spectrum steering in DSS-enabled networks.

翻译：动态频谱共享（DSS）允许灵活激活额外频谱资源，但留下了一个关键的运行时问题：当新频谱可用时，应选择哪种引导机制以最小化服务中断将已连接设备迁移至该频谱？我们通过连接至现网设备的调制解调器级跟踪数据，在12个城市区域四个月内收集的1600次执行记录中，首次实现了对3GPP标准用户设备引导机制的物理层感知表征，涵盖带宽部分（BWP）重配置、载波聚合（CA）、E-UTRA-NR双连接（EN-DC）、连接态切换（HO）以及释放与重定向（R&R）。通过将每种机制映射至可观测的物理层里程碑，我们将引导时延分解为以物理层为中心的固有执行组件与RRC至物理层完成组件，揭示了显著的异质性：NR BWP实现6.25毫秒平均时延且尾峰超过50毫秒为零，而CA的时延超过1225毫秒；移动性过程主要受调制解调器限制，而发现驱动机制则经历显著的RRC至物理层完成放大效应。基于这些测量结果，我们设计了POLARIS——一个基于O-RAN的系统，通过双参数中断评分选择中断最小的引导机制。与静态或非自适应基线相比，POLARIS将平均时延降低高达85.1%，T95时延降低89.7%，消除了超过50毫秒的尾峰，并避免了高中断机制，证明物理层执行分析能够为支持DSS的网络实现可靠且上下文感知的频谱引导。