Customized 5G and Beyond Private Networks with Integrated URLLC, eMBB, mMTC, and Positioning for Industrial Verticals
Permanent link to this recordhttp://hdl.handle.net/10754/677930
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AbstractThe fifth generation (5G) and beyond networks promote new business opportunities not only for mobile network operators but also for industrial verticals. However, most currently deployed 5G networks are public mobile networks developed for generalized purposes, limiting their adoption for various industrial fields demanding specialized quality of service. The new trend in applying 5G and beyond networks to industrial fields requires a new design paradigm shift calling for customized network structure, network resources, and network management. In customized 5G and beyond private networks (C5GBPN), network structure can be designed to be standalone or integrated; network resources can be designated to be exclusive or shared; and network management, including access control, data control, and governance, needs to be revisited. The flexibility of C5GBPN is of paramount importance for various application scenarios of industrial verticals, such as ultra-reliable low-latency communications, enhanced mobile broadband, massive machine-type communications, and positioning. In this regard, we first present the background and motivation of developing C5GBPN in this article. Then we provide three types of C5GBPN and discuss their pros and cons. Also, we provide feasible solutions to deal with these foreseeable design challenges of C5GBPN.
CitationGuo, S., Lu, B., Wen, M., Dang, S., & Saeed, N. (2022). Customized 5G and Beyond Private Networks with Integrated URLLC, eMBB, mMTC, and Positioning for Industrial Verticals. IEEE Communications Standards Magazine, 6(1), 52–57. https://doi.org/10.1109/mcomstd.0001.2100041
SponsorsSupported in part by the National Natural Science Foundation of China under Grant 62171262, in part by Shandong Provincial Natural Science Foundation under Grant ZR2021YQ47, in part by the Major Scientific and Technological Innovation Project of Shandong Province under Grant 2020CXGC010109, and in part by Stat Key Laboratory of Synthetical Automation for Process Industries under Grant 2020-KF-21-06.”