POLARIS: PHY-Aware Spectrum Steering for Dynamic Spectrum Sharing

TL;DR

This paper characterizes PHY-aware spectrum steering mechanisms in DSS, revealing latency heterogeneity and designing POLARIS to optimize mechanism selection, significantly reducing disruption and latency.

Contribution

It provides the first PHY-layer analysis of 3GPP-compliant steering mechanisms and introduces POLARIS, an adaptive system for minimal-disruption spectrum steering.

Findings

NR BWP achieves 6.25 ms mean latency with zero tail exceedance above 50 ms

Carrier Aggregation exceeds 1225 ms latency

POLARIS reduces mean latency by up to 85.1% and tail latency by 89.7%

Abstract

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.