Dynamic Measurement-Pilot Allocation for Low-Earth-Orbit Satellite Integrated Communication and Navigation

Abstract

Low Earth Orbit (LEO) satellite systems have potential to support integrated communication and navigation (ICaN) services. However, their rapid orbital motion makes resource allocation more difficult than in terrestrial or quasistatic satellite scenarios. In LEO-ICaN systems, the satelliteground channel quality and positioning geometry vary continuously, so a fixed measurement-pilot configuration cannot remain efficient throughout the service period. Allocating excessive pilot resources can improve measurement accuracy, but it reduces the resources available for communication data transmission. In contrast, insufficient pilot resources may degrade positioning accuracy when the Signal-to-Noise Ratio (SNR) or Geometric Dilution of Precision (GDOP) becomes unfavorable. To address this issue, this paper proposes a dynamic resource allocation scheme for LEO-ICaN systems. A Proximal Policy Optimization (PPO)-based agent is developed to adjust the pilot configuration according to real-time SNR and GDOP. The objective is to minimize pilot overhead and release more resource elements for communication data transmission while satisfying an allocated positioning error budget bounded by the theoretical CramérRao Lower Bound (CRLB). Simulation results show that the proposed scheme reduces the average pilot overhead by 46.82% compared with the conservative Fixed-High scheme while keeping the average CRLB below the 10-m threshold. Compared with the rule-based Tiered-Adaptive scheme, it achieves similar positioning accuracy with about 24.1% lower pilot overhead.