A Deep Reinforcement Learning Approach for RBMSCA in Optical Fiber Communication Networks

  • Xiao Zhang
  • , Qinghua Tian*
  • , Zuxian Li
  • , Fu Wang
  • , Feng Tian
  • , Sitong Zhou
  • , Qi Zhang
  • , Xiangjun Xin
  • *Corresponding author for this work

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

Abstract

A deep reinforcement learning framework is proposed to solve the problem of joint routing, modulation, band, core, and spectrum allocation in multiband, multicore elastic optical networks. The scheme outperforms several baseline reinforcement learning algorithms.

Original languageEnglish
Title of host publication2025 23rd International Conference on Optical Communications and Networks, ICOCN 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331548759
DOIs
Publication statusPublished - 2025
Externally publishedYes
Event23rd International Conference on Optical Communications and Networks, ICOCN 2025 - Zhangjiajie, China
Duration: 28 Jul 202531 Jul 2025

Publication series

Name2025 23rd International Conference on Optical Communications and Networks, ICOCN 2025

Conference

Conference23rd International Conference on Optical Communications and Networks, ICOCN 2025
Country/TerritoryChina
CityZhangjiajie
Period28/07/2531/07/25

Keywords

  • deep reinforcement learning
  • elastic optical networks
  • resource allocation

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