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AoI and Energy Minimization for LEO Satellite-Terrestrial Networks: A Constrained Multi-Objective Optimization Approach
Journal article   Peer reviewed

AoI and Energy Minimization for LEO Satellite-Terrestrial Networks: A Constrained Multi-Objective Optimization Approach

Qing Wei, Jia Shi, Zan Li, Zhongling Zhao and Tony Q.S. Quek
IEEE transactions on vehicular technology, Vol.74(8), pp.12436-12448
01/08/2025

Abstract

Attenuation Constrained multi-objective optimization Dynamic scheduling Energy consumption Interference Low earth orbit satellites matching theory NOMA Optimization resource allocation Resource management satellite communication Satellites Vehicle dynamics
In this paper, we investigate a LEO-satellite-terrestrial network designed to provide high-rate transmission services, on the constraints of limited energy and the stringent timeliness requirements of terrestrial user equipments (UEs). Specifically, we formulate the resource allocation problem for downlink LEO-to-ground transmissions, considering the optimization of user paring, transmit power, and beamwidth, for the sake of jointly minimizing the average Age of Information (AoI) and the average transmission energy consumption. By decoupling the problem, it develops an innovative matching algorithm for user pairing problem, followed by a multi-objective evolutionary algorithm with space division and coverage detection strategy (MOSC) for both optimizing power and beamwidth. These algorithms are executed iteratively with a relatively small number of iterations. Simulation results demonstrate the practical value of the proposed algorithm, showcasing its ability to accurately and efficiently utilize limited communication resources. Consequently, the proposed algorithm can outperform the advanced heuristic algorithms in terms of the convergence and diversity of the obtained non-dominated solutions.

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