Unlocking Unlicensed Band Potential to Enable URLLC in Cloud Robotics for Ubiquitous IoT

Bajracharya, Rojeena, Shrestha, Rakesh, Hassan, Syed Ali, Jung, Haejoon, Ansari, Rafay and Guizani, Mohsen (2021) Unlocking Unlicensed Band Potential to Enable URLLC in Cloud Robotics for Ubiquitous IoT. IEEE Network, 35 (5). pp. 107-113. ISSN 0890-8044

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Official URL: https://doi.org/10.1109/MNET.121.2100114

Abstract

Cloud robotics (CR) support extremely high reliability and low-latency communications in ubiquitous Internet of Things applications. However, many of those applications currently rely on wired connection, limiting their use within the confines of Ethernet/optical links. Some wireless solutions such as Wi-Fi have been considered, but failed to meet the stringent criteria for latency and outage. On the other hand, cellular technology possesses expensive licensing. Thus, the Third Generation Partnership Project (3GPP) is actively working on New Radio in the unlicensed band for incorporating ultra-reliable low-latency communications (URLLC) into fifth generation and beyond communication networks. In this article, we aim to study the feasibility of URLLC in an unlicensed band specifically for CR applications. We open up various use cases and opportunities offered by the unlicensed band in achieving latency and reliability constraints for robotics applications. We then review the regulatory requirements of unlicensed band operation imposed by 3GPP and explore its medium access challenges for CR due to the shared use of unstable wireless channels. Finally, we discuss the potential technology enablers to achieve URLLC using the unlicensed band for the ubiquitous CR applications.

Item Type: Article
Additional Information: Funding information:This research was supported by the Ministry of Science and ICT, Korea, in part under the Information Technology Research Center support program (IITP-2021-0-02046) supervised by the Institute for Information & Communications Technology Planning & Evaluation, and in part under Grant NRF 2020H1D3A1A02080428 supervised by the National Research Foundation of Korea.
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 07 Dec 2021 11:18
Last Modified: 07 Dec 2021 11:30
URI: http://nrl.northumbria.ac.uk/id/eprint/47916

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