Continuous Aperture Array-Assisted Integrated Communication and Navigation in LEO Satellite Constellations

2026-07-09

AI Summary

This study addresses the performance coupling and resource contention challenges arising from spectrum sharing between communication and navigation in low Earth orbit satellite constellations. To this end, it introduces, for the first time, a continuous-aperture array-based integrated sensing and communication framework. By developing a multi-satellite cooperative electromagnetic transmission model, the proposed approach jointly optimizes dual-functional beamforming to simultaneously transmit communication and navigation signals over the shared spectrum. Innovatively combining channel subspace dimensionality reduction with Cramér-Rao bound analysis, the method transforms an infinite-dimensional optimization problem into a tractable finite-dimensional form, which is then solved via an iterative convex optimization algorithm. Experimental results demonstrate that the proposed scheme significantly enhances positioning accuracy while maintaining communication data rates, outperforming conventional discrete phased arrays and other baseline approaches.

Abstract

This paper proposes a novel continuous aperture array (CAPA)-assisted integrated communication and navigation (ICAN) framework for low Earth orbit (LEO) satellite constellations. Within this framework, an electromagnetic-based collaborative transmission model is developed, in which multiple satellites equipped with CAPAs simultaneously radiate downlink data streams and navigation reference signals over shared spectrum. Building upon this, the achievable communication rate and the navigation Cramer-Rao bound (CRB) are derived, which explicitly characterize the intrinsic coupling between the dual-function beamformers and system performance. To improve the positioning accuracy with communication quality of service guarantee, a joint beamforming optimization problem is formulated to minimize the average CRB subject to transmit power budgets and minimum rate constraints. To tackle the inherent infinite-dimensionality of the CAPA beamformer design, an ICAN channel subspace is introduced to equivalently transform the formulation into a tractable finite-dimensional problem, which is then efficiently solved via an iterative convex optimization algorithm. Finally, numerical results demonstrate that the proposed CAPA-assisted beamforming design algorithm significantly outperforms conventional discrete phased array architectures and other benchmark schemes, yielding notable improvements in ICAN performance.

Problem

• Integrated Communication and Navigation
• LEO Satellite Constellations
• Positioning Accuracy
• Communication Quality of Service
• Beamforming

Innovation

• continuous aperture array
• integrated communication and navigation
• LEO satellite constellations
• beamforming optimization
• Cramer-Rao bound