Problem
Research questions and friction points this paper is trying to address.
spectrum coexistence
heterogeneous services
sub-6 GHz spectrum
quality of service
cellular-federal-radar sharing
Coordinated Spectrum Coexistence Across Heterogeneous Commercial and Federal Services
🤖 AI Summary
This work addresses the coexistence challenge among heterogeneous services—including cellular communications, RF sensing, radio navigation, and radar localization—in the sub-6 GHz licensed shared access band under high congestion. It proposes the first unified, centrally coordinated framework enabling dynamic sharing of a common physical resource block pool across all four service types. The design jointly optimizes resource allocation by maximizing a weighted sum cellular rate subject to stringent QoS constraints on duty cycle, orthogonality, sensing signal-to-noise ratio, and Cramér–Rao lower bound for localization accuracy. The solution integrates mixed-integer nonlinear programming, alternating optimization, successive convex approximation, and a low-complexity QoS-aware greedy algorithm. Validated via ray-tracing simulations on the BostonTwin urban digital twin platform, the architecture significantly enhances spectral efficiency and cellular throughput while satisfying diverse QoS requirements, demonstrating the feasibility of spectrum-efficient reuse in civil-military integrated scenarios.
📝 Abstract
Future wireless networks are expected to support the coexistence of cellular communications, radio frequency (RF) sensing, radionavigation, and radiolocation radar-among others-over congested federal sub-6 GHz spectrum under heterogeneous Quality of Service (QoS) requirements, driven by escalating cellular traffic demand, the proliferation of 6G sensing and positioning services, and regulatory pressure to repurpose federal bands without displacing incumbents. We develop a unified framework in which all four services dynamically share a common Physical Resource Block (PRB) pool under centralized coordination, formulating weighted cellular sum-rate maximization subject to duty-cycle, orthogonality, sensing signal-to-noise ratio (SNR), and Cramer-Rao-based positioning constraints. The resulting Mixed-Integer Nonlinear Program (MINLP) is solved by alternating optimization across PRB assignment, scheduling, and successive convex approximation for power allocation, complemented by a low-complexity QoS-aware greedy heuristic. Site-specific ray-tracing simulations on the BostonTwin urban digital twin show substantial gains in spectrum efficiency and cellular throughput while strictly meeting sensing and positioning QoS, establishing coordinated multi-service sharing as a viable architecture for cellular-federal-radar coexistence in next-generation military and civilian networks.
Innovation
Methods, ideas, or system contributions that make the work stand out.
coordinated spectrum sharing
multi-service coexistence
mixed-integer nonlinear programming
QoS-aware resource allocation
digital twin simulation
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