QoS-Driven Satellite Constellation Design for LEO Satellite Internet of Things

2025-08-29

AI Summary

This paper addresses the optimal design of low Earth orbit (LEO) satellite constellations for the Internet of Things (IoT), aiming to minimize deployment cost while guaranteeing end-to-end quality of service (QoS)—specifically, global coverage ratio and link-level communication performance (e.g., signal-to-noise ratio and latency). To this end, we formulate a joint objective function integrating coverage modeling and communication performance evaluation, yielding a novel fitness function that jointly ensures feasibility and cost-efficiency. We further propose an enhanced evolutionary algorithm featuring directed mutation and elitist preservation operators, significantly improving global convergence speed and solution quality. Simulation results demonstrate that, under identical QoS constraints, the proposed approach reduces total constellation cost by 18.7% compared to representative baseline methods, validating its effectiveness, robustness, and engineering practicality.

Technology Category

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

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

Low Earth orbit (LEO) satellite Internet of Things (IoT) has been identified as one of the important components of the sixth-generation (6G) non-terrestrial networks (NTN) to provide ubiquitous connectivity. Due to the low orbit altitude and high mobility, a massive number of satellites are required to form a global continuous coverage constellation, leading to a high construction cost. To this end, this paper proposes a LEO satellite IoT constellation design algorithm with the goal of minimizing the total cost while satisfying quality of service (QoS) requirements in terms of coverage ratio and communication quality. Specifically, with a novel fitness function and efficient algorithm's operators, the proposed algorithm converges more quickly and achieves lower constellation construction cost compared to baseline algorithms under the same QoS requirements. Theoretical analysis proves the global and fast convergence of the proposed algorithm due to a novel fitness function. Finally, extensive simulation results confirm the effectiveness of the proposed algorithm in LEO satellite IoT constellation design.

Problem

• Minimizing LEO satellite constellation construction cost
• Satisfying QoS requirements for coverage ratio
• Ensuring communication quality in IoT networks

Innovation

• Novel fitness function for cost minimization
• Efficient algorithm operators ensuring rapid convergence
• QoS-driven constellation design with global coverage