Deep Reinforcement Learning for BBU Placement and Routing in C-RAN

Zhengguang Gao, Jiawei Zhang, Shuangyi Yan, Yuming Xiao, Dimitra Simeonidou, Yuefeng Ji

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

7 Citations (Scopus)
235 Downloads (Pure)

Abstract

The paper proposes a deep reinforcement learning (DRL) based policy for BBU placement and routing in C-RAN. The simulation results show DRL-based policy reaches the near-optimal performance with a significantly reduced computing time.

Original languageEnglish
Title of host publication2019 Optical Fiber Communications Conference and Exhibition, OFC 2019 - Proceedings
Place of PublicationSan Diego
PublisherOptical Society of America (OSA)
Number of pages3
ISBN (Electronic)9781943580538
ISBN (Print)9781943580538
DOIs
Publication statusPublished - 22 Apr 2019
Event2019 Optical Fiber Communications Conference and Exhibition, OFC 2019 - San Diego, United States
Duration: 3 Mar 20197 Mar 2019

Conference

Conference2019 Optical Fiber Communications Conference and Exhibition, OFC 2019
CountryUnited States
CitySan Diego
Period3/03/197/03/19

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  • Cite this

    Gao, Z., Zhang, J., Yan, S., Xiao, Y., Simeonidou, D., & Ji, Y. (2019). Deep Reinforcement Learning for BBU Placement and Routing in C-RAN. In 2019 Optical Fiber Communications Conference and Exhibition, OFC 2019 - Proceedings [W2A.22] Optical Society of America (OSA). https://doi.org/10.1364/OFC.2019.W2A.22