Joint Satellite Power Consumption and Handover Optimization for LEO Constellations

2025-11-24

AI Summary

Frequent satellite-to-ground handovers caused by dynamic topologies in low Earth orbit (LEO) satellite constellations severely degrade system performance and incur substantial signaling overhead and energy consumption. Method: This paper proposes a handover-aware joint optimization framework to maximize the total downlink throughput, simultaneously optimizing user–satellite association and power allocation while explicitly incorporating handover-induced signaling and power penalties into the formulation. Unlike conventional nearest-satellite association policies, we formulate the problem as a mixed-integer convex programming (MICP) model, enabling global optimization via off-the-shelf commercial solvers. Contribution/Results: Extensive Monte Carlo simulations demonstrate that, under large-scale LEO constellation scenarios, the proposed method improves aggregate user throughput by approximately 40% without significantly increasing handover frequency. Consequently, it substantially reduces system overhead and enhances resource scheduling efficiency.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Security and Privacy: Large-scale security measurements

Abstract

In satellite constellation-based communication systems, continuous user coverage requires frequent handoffs due to the dynamic topology induced by the Low Earth Orbit (LEO) satellites. Each handoff between a satellite and ground users introduces additional signaling and power consumption, which can become a significant burden as the size of the constellation continues to increase. This work focuses on the optimization of the total transmission rate in a LEO-to-user system, by jointly considering the total transmitted power, user-satellite associations, and power consumption, the latter being handled through a penalty on handoff events. We consider a system where LEO satellites serve users located in remote areas with no terrestrial connectivity, and formulate the power allocation problem as a mixed-integer concave linear program (MICP) subject to power and association constraints. Our approach can be solved with off-the-shelf solvers and is benchmarked against a naive baseline where users associate to their closest visible satellite. Extensive Monte Carlo simulations demonstrate the effectiveness of the proposed method in controlling the handoff frequency while maintaining high user throughput. These performance gains highlight the effectiveness of our handover-aware optimization strategy, which ensures that user rates improve significantly, by about 40%, without incurring a disproportionate rise in the handoff frequency.

Problem

• Optimizing LEO satellite power consumption and handover frequency
• Improving transmission rates while controlling handoff signaling burden
• Solving power allocation as mixed-integer program for remote users

Innovation

• Joint optimization of power consumption and handover
• Formulating power allocation as mixed-integer program
• Handover-aware strategy improves rates by 40%