Bouhafs, F, Raschella, A, MacKay, M, Hashem Eiza, M and Hartog, FD (2024) Optimizing Radio Access for Massive IoT in 6G Through Highly Dynamic Cooperative Software-Defined Sharing of Network Resources. Future Internet, 16 (12).

Preview

Text Optimizing Radio Access for Massive IoT in 6G Through Highly Dynamic Cooperative Software-Defined Sharing of Network Resources.pdf - Published Version Available under License Creative Commons Attribution. Download (7MB) | Preview

Abstract

6G will provide an opportunity to build on and expand the vertical use cases currently supported by 5G. The Internet of Things (IoT) has been a major component for many of these use cases. Moving forward, 6G will need to connect more IoT devices than 5G, often densely deployed in urban areas. This makes simply accessing the wireless medium an issue as current generation networks are not designed to support many thousands of devices in each other’s vicinity, attempting to send/receive data simultaneously. In this paper, we present a model and a 6G system architecture for trading wireless network resources in massive IoT scenarios inspired by the concept of Sharing Economy, using the novel concept of spectrum programming. We simulated a truly massive IoT network and evaluated the scalability of the system when managed using our platform compared to standard fifth generation (5G) deployments. The experiments show how the proposed scheme can improve network resource allocation by up to 80% when compared to standard 5G allocation solutions. This is accompanied by similar improvements in interference and device energy consumption. Finally, we performed evaluations that demonstrate how the proposed platform can benefit all the stakeholders that decide to join the scheme.

Item Type:	Article
Uncontrolled Keywords:	6G; Massive IoT; Blockchain; Sharing Economy; Spectrum Access; Spectrum Programming
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Computer Science and Mathematics
Publisher:	MDPI
SWORD Depositor:	A Symplectic
Date Deposited:	22 Nov 2024 15:37
Last Modified:	06 Dec 2024 15:15
DOI or ID number:	10.3390/fi16120442
URI:	https://researchonline.ljmu.ac.uk/id/eprint/24844

View Item