A Throughput Optimization in Space-air-ground Integrated Networks

DU Danbing

doi:10.15892/j.cnki.djzdxb.2023.05.017

Journal of Projectiles, Rockets, Missiles and Guidance >

2023 , Vol. 43 >Issue 5: 109 - 114

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2023.05.017

A Throughput Optimization in Space-air-ground Integrated Networks

DU Danbing

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College of Education, Changchun Normal University, Changchun 130032, Jilin, China

Received date: 2022-06-22

Online published: 2024-12-30

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Abstract

In order to improve throughput of Space-Air-Ground Integrated Networks, Reinforcement Learning-based Link Optimization (RLLO) algorithm is proposed in this paper. In RLLO algorithm, we consider low Earth orbit satellites as an effective backhaul solution. For access links, we manage the radio resource among UAVs and small cell base stations and optimize the trajectories of unmanned Aerial Vehicles in order to improve the throughput. The objective problem of backhaul and access link is constructed. Then, we utilize the tools of reinforcement, and proposed approach based on the multi-armed bandit algorithm. Simulation results show that the proposed RLLO algorithm improve the throughput and rate of user.

Key words： space-air-ground integrated networks; low earth orbit; reinforcement learning; access link; multi-armed bandit

Cite this article

DU Danbing . A Throughput Optimization in Space-air-ground Integrated Networks[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2023 , 43(5) : 109 -114 . DOI: 10.15892/j.cnki.djzdxb.2023.05.017

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