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Analysis on the Neural Network-aided Satellite Resource Allocation Schemes

  • Gyuseong Jo*
  • , Satya Chan
  • , Sooyoung Kim
  • , Daesub Oh
  • *Corresponding author for this work
  • National University
  • Electronics and Telecommunications Research Institute

Research output: Contribution to conferenceConference paperpeer-review

Abstract

Satellite systems can efficiently utilize expensive and limited bandwidth and power resources, by reusing frequency bands over multibeams with provision of optimum resource allocation. This paper provides comparative analysis on the resource allocation schemes for frequency reusing multibeam satellite systems under interference-limited condition. After reviewing recent works on machine learning-aided schemes, we propose a new idea to enhance the performance. The performance estimation results investigated in this paper reveal that the proposed scheme can enhance the performance compared to the existing method.

Original languageEnglish
Title of host publication2023 International Conference on Electronics, Information, and Communication, ICEIC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350320213
DOIs
StatePublished - 2023
Event2023 International Conference on Electronics, Information, and Communication, ICEIC 2023 - Singapore, Singapore
Duration: 2023.02.52023.02.8

Publication series

Name2023 International Conference on Electronics, Information, and Communication, ICEIC 2023

Conference

Conference2023 International Conference on Electronics, Information, and Communication, ICEIC 2023
Country/TerritorySingapore
CitySingapore
Period23.02.523.02.8

Keywords

  • neural network
  • resource allocation
  • satellite

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