Parametric Precoding Based on Improved Dynamic Gradient Descent in Multibeam Satellite Communications

Jiayu Wang, Rugui Yao, Donghui Xu, Ye Fan, Xiaoya Zuo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Precoding and beamforming have been studied in multibeam satellite. In this paper, we propose a precoding method based on dynamic gradient descent, which is suitable for large array antenna and multiuser multibeam satellite environment. This method doesn't need complex vector or matrix design because of combining zero-forcing and maximum ratio transmission. And gradient descent algorithm is used to solve this combining zero-forcing and maximum ratio transmission model. Meanwhile, the convergence of gradient descent is also proved. The simulation results show that the improved gradient descent based on parametric design can get higher sum rate, whether it is in the case of multiple users with massive antennas or small users with a few number of antennas. Meanwhile, for the gradient descent convergence problem, we propose a dynamic adaptive learning rate updating method, which has faster and better convergence performance than traditional gradient descent algorithm.

Original languageEnglish
Title of host publication32nd Wireless and Optical Communications Conference, WOCC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350337150
DOIs
StatePublished - 2023
Event32nd Wireless and Optical Communications Conference, WOCC 2023 - Newark, United States
Duration: 5 May 20236 May 2023

Publication series

Name32nd Wireless and Optical Communications Conference, WOCC 2023

Conference

Conference32nd Wireless and Optical Communications Conference, WOCC 2023
Country/TerritoryUnited States
CityNewark
Period5/05/236/05/23

Keywords

  • beamforming
  • Gradient descent algorithm
  • multibeam satellite
  • precoding

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