Star-earth cooperative network channel allocation algorithm based on power grid and deep learning

Jigao Song; Jian Xu; Xuanzhong Wang; Haitao Xu

doi:10.1117/12.3032335

12 July 2024 Star-earth cooperative network channel allocation algorithm based on power grid and deep learning

Jigao Song, Jian Xu, Xuanzhong Wang, Haitao Xu

Proceedings Volume 13185, International Conference on Communication, Information, and Digital Technologies (CIDT2024) ; 131850E (2024) https://doi.org/10.1117/12.3032335
Event: International Conference on Communication, Information and Digital Technologies, 2024, Wuhan, China

Abstract

The star earth collaboration network private network can make up for the problems of poor signal coverage, limited bandwidth, low security and high cost that exist in the existing wireless public network. It can provide reliable and stable power system communications. However, the star-earth collaborative network suffers from resource constraints due to limited on-planet spectrum resources, power, computation and storage resources. Therefore, how to allocate these limited channel resources reasonably and efficiently, it is especially important to improve the resource utilization and system performance. Based on this, we establish a star-earth collaborative network architecture to meet the application of power scenarios. To improve the resource allocation efficiency of this network architecture, we model the channel allocation process by sensing the channel allocation state and beam user service request state in the environment through the satellite intelligences of the star-earth collaboration network. And then, we propose a dynamic channel allocation algorithm based on deep learning. We design state, action and reward functions for feedback optimization of channel resource allocation strategy based on deep learning, and a deep learning based channel resource allocation method is proposed to realize the optimal allocation of system channel resources. In the proposed method, the corresponding channel resources for users is allocated based on the channel allocation policy, and environment-based reward gain information is given to optimally update the channel allocation policy. The related simulation results show that our proposed channel resource allocation algorithm for star-terrestrial collaborative network has lower service blocking rate and higher channel utilization than other assistant allocation algorithms.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jigao Song, Jian Xu, Xuanzhong Wang, and Haitao Xu "Star-earth cooperative network channel allocation algorithm based on power grid and deep learning", Proc. SPIE 13185, International Conference on Communication, Information, and Digital Technologies (CIDT2024) , 131850E (12 July 2024); https://doi.org/10.1117/12.3032335

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Satellites

Deep learning

Network architectures

Antennas

Mathematical optimization

Telecommunications

Satellite communications

Show All Keywords

Keywords/Phrases

Search In:

Publication Years