Z. Da, K. Yang, V. Sridharan, J. Huang, E. Kurniawan, V. P. Kafle, T. Miyazawa, T. Hirayama, and M. Jibiki, "Multi-Objective Evolutionary Algorithm-based Resource Allocation for Integrated TN-NTN," IEEE Globecom 2025, In Proceedings, December 2025.
Abstract:
This paper investigates the resource allocation problem in an integrated Terrestrial Network (TN) - Non-Terrestrial Network (NTN) composed of satellites, unmanned aerial vehicles (UAVs), and ground stations (gNodeB). The objective is to jointly maximize the total system throughput and improve user fairness under a variety of physical and service constraints. To this end, we propose MOEA/DADE algorithm, an improved Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) that integrates historical solution preservation, dynamic search direction adjustment, and multi-strategy mutation mechanisms. Simulation results demonstrate that the proposed algorithm outperforms traditional Genetic Algorithm (GA) and standard MOEA/D in terms of Pareto front quality, throughput, efficiency, fairness, and the Hypervolume (HV) metric, validating its effectiveness and robustness in complex TN-NTN scenarios.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the National Research Foundation, Infocomm Media Development Authority - Future Communications Programme
Grant Reference no. : FCP-ASTAR-IRC-2025-003