Positioning-Aided Channel Estimation for Multi-LEO Satellite Cooperative Beamforming

TL;DR

This work tackles the challenge of channel estimation in multi-LEO satellite networks by introducing a two-timescale pace framework that integrates downlink positioning with uplink channel estimation and downlink cooperative beamforming. By exploiting the distinct variation rates of position-related parameters and channel gains, the authors derive MCRB-based performance bounds under practical clock bias and CFO impairments and demonstrate how UT position information enhances uplink channel estimation even with errors. A low-complexity cooperative beamforming algorithm is developed to overcome single-satellite link-budget limitations, enabling near-optimal downlink rates under nominal CSI. Numerical results validate the framework, showing robust downlink positioning, improved uplink estimation, and significant gains in downlink throughput when employing multi-LEO cooperation and pace-based CSI. The approach promises practical benefits for NTN systems by improving positioning accuracy, reducing pilot overhead, and facilitating scalable beamforming in large satellite constellations.

Abstract

We investigate a multi-low Earth orbit (LEO) satellite system that simultaneously provides positioning and communication services to terrestrial user terminals. To address the challenges of accurately acquiring channel state information in LEO satellite systems, we propose a novel two-timescale positioning-aided channel estimation framework, exploiting the distinct variation rates of position-related parameters and channel gains inherent in LEO satellite channels. Using the misspecified Cramér-Rao bound (MCRB) theory, we systematically analyze positioning performance under practical imperfections, such as inter-satellite clock bias and carrier frequency offset. Furthermore, we theoretically demonstrate how position information derived from downlink positioning can enhance uplink channel estimation accuracy, even in the presence of positioning errors, through an MCRB-based analysis. To address the limited link budgets and communication rates of single-satellite communication, we develop a multi-LEO cooperative beamforming strategy for downlink transmission that leverages cluster-wise satellite cooperation while maintaining reduced complexity. Theoretical analyses and numerical results confirm the effectiveness of the proposed framework in facilitating high-precision downlink positioning under practical imperfections, facilitating uplink channel estimation, and enabling efficient downlink communication.

Figures (9)

• Figure 1: A cluster of LEO satellites traverses orbit while simultaneously delivering positioning and communication services to UTs. Each UT is served by all LEO satellites within the cluster for both functionalities. Positioning operations in the downlink occur over a relatively large timescale, whereas uplink channel estimation and downlink communication are carried out on a smaller timescale. The specific definitions of these timescales will be clarified later.
• Figure 2: Illustration of the two-timescale frame structure, where each large-timescale frame encompasses multiple small-timescale subframes. The large-timescale frame is governed by the position-coherent time, while the small-timescale subframe is defined by the channel gain-coherent time.
• Figure 3: Positioning rmse lb versus per-leo satellite power budget.
• Figure 4: Positioning rmse lb versus maximum clock bias and cfo.
• Figure 5: Uplink channel estimation rmse lb versus positioning error: (a) Channel vector estimation; (b) toa estimation.