A robust routing strategy based on deep reinforcement learning for mega satellite constellations

Abstract For mega satellite constellations, it has been a great challenge to achieve global routing and guarantee the performance of inter‐satellite transmission. To address the problem, a robust routing strategy based on deep reinforcement learning is proposed in this letter. The proposed method is...

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Bibliographic Details
Main Authors: Ke Chu, Sixi Cheng, Lidong Zhu
Format: Article
Language:English
Published: Wiley 2023-06-01
Series:Electronics Letters
Subjects:
Online Access:https://doi.org/10.1049/ell2.12820
Description
Summary:Abstract For mega satellite constellations, it has been a great challenge to achieve global routing and guarantee the performance of inter‐satellite transmission. To address the problem, a robust routing strategy based on deep reinforcement learning is proposed in this letter. The proposed method is applicable to degraded transmission performance, which exhibits better conformity to real‐world scenarios. Moreover, the age of information (AoI) of packets are utilized as one of the multi‐optimization targets to ensure the effectiveness of message transmission throughout the network. Numerical simulations show the outstanding average AoI performance of the proposed method and its greater robustness to jamming compared to existing methods. Meanwhile, it is also more effective for utilizing resources.
ISSN:0013-5194
1350-911X