Service Multiplexing and Revenue Maximization in Sliced C-RAN Incorporated With URLLC and Multicast eMBB

Jianhua Tang, Byonghyo Shim*, Tony Q.S. Quek

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    171 Citations (Scopus)

    Abstract

    The fifth generation (5G) wireless system aims to differentiate its services based on different application scenarios. Instead of constructing different physical networks to support each application, radio access network (RAN) slicing is deemed as a prospective solution to help operate multiple logical separated wireless networks in a single physical network. In this paper, we incorporate two typical 5G services, i.e., enhanced Mobile BroadBand (eMBB) and ultra-reliable low-latency communications (URLLC), in a cloud RAN (C-RAN), which is suitable for RAN slicing due to its high flexibility. In particular, for eMBB, we make use of multicasting to improve the throughput, and for URLLC, we leverage the finite blocklength capacity to capture the delay accurately. We envision that there will be many slice requests for each of these two services. Accepting a slice request means a certain amount of revenue (consists of long-term revenue and shot-term revenue) is earned by the C-RAN operator. Our objective is to maximize the C-RAN operator's revenue by properly admitting the slice requests, subject to the limited physical resource constraints. We formulate the revenue maximization problem as a mixed-integer nonlinear programming and exploit efficient approaches to solve it, such as successive convex approximation and semidefinite relaxation. Simulation results show that our proposed algorithm significantly saves system power consumption and receives the near-optimal revenue with an acceptable time complexity.

    Original languageEnglish
    Article number8638932
    Pages (from-to)881-895
    Number of pages15
    JournalIEEE Journal on Selected Areas in Communications
    Volume37
    Issue number4
    DOIs
    Publication statusPublished - 2019 Apr

    Bibliographical note

    Funding Information:
    This work was supported in part by the Korea Research Fellowship Program through the National Research Foundation of Korea (NRF) through the Ministry of Science and Information and Communications Technology under Grant 2016H1D3A1938245, in part by the NRF grant through the Korean Government (MSIP) under Grant 2014R1A5A1011478, in part by the Singapore University of Technology and Design-Zhejiang University (SUTD-ZJU) Research Collaboration under Grant SUTDZJU/ RES/01/2016, and in part by the SUTD-ZJU Research Collaboration under Grant SUTD-ZJU/RES/05/2016.

    Funding Information:
    Manuscript received June 21, 2018; revised December 6, 2018; accepted January 25, 2019. Date of publication February 11, 2019; date of current version March 15, 2019. This work was supported in part by the Korea Research Fellowship Program through the National Research Foundation of Korea (NRF) through the Ministry of Science and Information and Communications Technology under Grant 2016H1D3A1938245, in part by the NRF grant through the Korean Government (MSIP) under Grant 2014R1A5A1011478, in part by the Singapore University of Technology and Design-Zhejiang University (SUTD-ZJU) Research Collaboration under Grant SUTD-ZJU/RES/01/2016, and in part by the SUTD-ZJU Research Collaboration under Grant SUTD-ZJU/RES/05/2016. Part of this paper [1] will be presented at the 53rd IEEE International Conference on Communications (ICC), Shanghai, China, May 2019. (Corresponding author: Byonghyo Shim.) J. Tang and B. Shim are with the Institute of New Media and Communications, Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, South Korea (e-mail: [email protected]; [email protected]).

    Publisher Copyright:
    © 2019 IEEE.

    Keywords

    • C-RAN
    • URLLC
    • eMBB
    • multicast
    • network slicing

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Electrical and Electronic Engineering

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