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

## TL;DR

This paper introduces a cost-effective LEO satellite IoT constellation design algorithm that ensures QoS requirements, featuring a novel fitness function and efficient operators for faster convergence and lower costs.

## Contribution

It presents a new algorithm with a unique fitness function for designing LEO satellite IoT constellations, optimizing cost and QoS, with proven theoretical convergence.

## Key findings

- The proposed algorithm converges faster than baseline methods.
- It achieves lower constellation construction costs under the same QoS.
- Simulation results validate the algorithm's effectiveness in practical scenarios.

## 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.