PreHO: Predictive Handover for LEO Satellite Networks

2026-03-09

AI Summary

This work addresses the high signaling overhead and latency incurred by conventional handover mechanisms in low Earth orbit (LEO) satellite networks, which stem from the rapid movement of satellites. Leveraging the relative static nature of user terminals and the predictability of channel conditions, the paper proposes a predictive handover mechanism that shifts the paradigm from reactive, event-triggered handovers to proactive, pre-planned transitions. An iterative algorithm combining alternating optimization and dynamic programming is developed to efficiently compute the optimal handover strategy. Experimental evaluations based on real-world data demonstrate that the proposed approach significantly reduces both signaling overhead and handover latency, yielding markedly improved user experience compared to traditional methods.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Multiagent Systems: Mechanism Design

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Low-Earth Orbit (LEO) Satellite Networks (LSNs) offer a promising solution for extending connectivity to areas not covered by Terrestrial Networks (TNs). However, the rapid movement, broad coverage, and high communication latency of LEO satellites pose significant challenges to conventional handover mechanisms, resulting in unacceptable signaling overhead and handover latency. To address these issues, this paper identifies a fundamental difference between the mobility patterns in LSNs and TNs: users are typically stationary relative to the fast- moving satellites, and channel states in LSNs are often stable and predictable. This observation enables handovers to be planned in advance rather than triggered reactively. Motivated by this insight, we propose PreHO, a predictive handover mechanism tailored for LSNs that proactively determines optimal handover strategies, thereby simplifying the handover process and enhancing overall efficiency. To optimize the pre-planned handover decisions, we further formulate the handover planning problem and develop an efficient iterative algorithm based on alternating optimization and dynamic programming. Extensive evaluations driven by real-world data demonstrate that PreHO significantly outperforms traditional handover schemes in terms of signaling overhead, handover latency, and user experience.

Problem

• LEO satellite networks
• handover
• signaling overhead
• handover latency
• mobility patterns

Innovation

• Predictive Handover
• LEO Satellite Networks
• Handover Optimization
• Alternating Optimization
• Dynamic Programming