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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publication2019 Optical Fiber Communications Conference and Exhibition, OFC 2019 - Proceedings
Place of PublicationSan Diego
Publisher or commissioning bodyOptical Society of America (OSA)
Number of pages3
ISBN (Electronic)9781943580538
ISBN (Print)9781943580538
DOIs
DateAccepted/In press - 6 Dec 2018
DatePublished (current) - 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

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.

Event

2019 Optical Fiber Communications Conference and Exhibition, OFC 2019

Duration3 Mar 20197 Mar 2019
CitySan Diego
CountryUnited States
Sponsors3M Science Applied to Life (External organisation), AC Photonics, Inc. (External organisation), Acacia Communications, Inc. (External organisation), AIM Photonics (External organisation), Alibaba Group (External organisation), et al. (External organisation)

Event: Conference

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  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Optical Society of America at https://www.osapublishing.org/abstract.cfm?URI=OFC-2019-W2A.22 . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 774 KB, PDF document

DOI

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