5G-Wi-SUN for Building Management System

Hoo, F., Tan, F. S. L., Chan, R. C. B., Waszecki, P., Keoh, S. L. , Seow, C. K. , Li, D., Cao, Q. and Sum, C. S. (2023) 5G-Wi-SUN for Building Management System. In: 6th International Conference on Applied Computational Intelligence in Information Systems, Bandar Seri Begawan, Brunei, 23-25 Oct 2023, ISBN 9798350317428 (doi: 10.1109/ACIIS59385.2023.10367377)

Abstract

With higher data rates and lower latency, 5G constitutes a mobile alternative to both wired networks and less capable wireless solutions. However, the performance of 5G requires expensive hardware and high energy consumption, making it less suitable for energy-constrained edge devices. Combining the capabilities of 5G for Wide Area Network (WAN) access, with the benefits of other wireless networks purpose-built for low-power embedded systems, a Building Management System (BMS) based on 5G can be deployed anywhere in a building with 5G coverage extended with a suitable LPWAN connectivity for IoT devices of the BMS. In this paper, the LPWAN of choice is the Wireless Smart Utility Network (Wi-SUN), a low-power sub-GHz connectivity based on IEEE 802.15.4g, offering mesh and multi-hop features for improved reliability and range, alongside competitive data rates. The performance of a 5G-Wi-SUN hybrid network was evaluated with a fibre-broadband hybrid network, a 5G-only network and a Wi-SUN-only network to determine the feasibility of 5G-Wi-SUN network. Test results show a significant performance of our 5G-WiSUN network, with a round-trip times below half a second in most cases, and a trimean of 115ms, only 27ms more than the fibre broadband-WiSUN network in our experiment. Consequently, the results have demonstrated the ability of a 5G-Wi-SUN network to provide a versatile alternative to fibre broadband-WiSUN, while maintaining a comparable performance.

• Item Type: Conference Proceedings
• Additional Information: We gratefully acknowledge the funding support from Singapore IMDA and NRF Future Communications R and D Programme (FCP) Grant Award No. FCP-SIT-TG-2022-006.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Cao, Dr Qi and Keoh, Dr Sye Loong and Li, Dr David and Seow, Dr Chee Kiat
• Authors: Hoo, F., Tan, F. S. L., Chan, R. C. B., Waszecki, P., Keoh, S. L., Seow, C. K., Li, D., Cao, Q., and Sum, C. S.
• College/School: College of Science and Engineering; College of Science and Engineering > School of Computing Science
• ISBN: 9798350317428
• Copyright Holders: Copyright: © 2023 IEEE
• First Published: First published in 6th International Conference on Applied Computational Intelligence in Information Systems (ACIIS), 2023
• Publisher Policy: Reproduced in accordance with the publisher copyright policy