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Leicester UK Scientists Use AI and Terahertz to Boost 5G and 6G IoT Connectivity

Monday, Nov 20th, 2023 (11:04 am) - Score 360
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A new technology has been created by a team of computer scientists at the University of Leicester (UL), which could improve speed and power consumption for users of mobile devices, particularly Internet of Things (IoT) sensors, and may help reap the benefits from the next generation of mobile broadband technology, 6G.

Just to be clear, the focus of this research appears to have been on fronthaul connectivity (i.e. the links between remote cell sites and the baseband unit), rather than backhaul (e.g. the wired capacity link to a mobile network), which helps to explain why anything involving Terahertz (THz) bands would make sense for IoT devices. Such signals can carry a lot of data, but they’re normally far too weak to travel very far.

NOTE: The study forms part of the EU-funded 6G BRAINS project, which will develop an AI-driven self-learning platform to intelligently and dynamically allocate resources, enhancing capacity and reliability, and improving positioning accuracy while decreasing latency of response.

In this case, the novel technology is designed to manage demands on mobile networks from multiple users using THz frequencies (expected to form a part of the future 6G standard), while also harnessing a new technique known as Multicarrier-Division Duplex (MDD), which allows a receiver in the network to be nearly free of self-interference in the digital domain by relying only on the Fast Fourier Transform (FFT) processing.

The new solution appears to overcome some of the “self-interference problem” problem that can occur on modern 5G networks, which stems from the increasing demands of more users and devices, but can result in slower connections and costly energy consumption (particularly with future industrial applications of massive scale and varying demands).

This project proposed a novel technology to optimise the assignment of subcarrier set and the number of access point clusters and improve the communication quality in different networks. The team tested their technology in a simulation based on a real-world industrial setting, finding that it out-performed existing technologies. A 10% power consumption reduction can be achieved, compared to other state of the art technologies,” said the research.

Professor Huiyu Zhou, UL School of Computing and Mathematical Sciences, said:

“With our proposed technology, 5G/6G systems require less energy consumption, have faster device selection and less resource allocation. Users may feel their mobile communication is quicker, wider and with reduced power demands.

The University of Leicester is leading the development of AI solutions for device selection and access point clustering. AI technologies, reinforcement learning in particular, help us to search for the best parameters used in the proposed wireless communication systems quickly and effectively. This helps to save power, resources and human labour. Without using AI technologies, we will spend much more time on rendering the best parameters for system set-up and device selection in the network.”

The team is now continuing work on optimising the proposed technologies and reducing the computational complexity of the technique, which is currently one of the key challenges. The source code of the proposed method has also been published and shared with the entire world for promoting the research.

The related research paper – ‘MDD-Enabled Two-Tier Terahertz Fronthaul in Indoor Industrial Cell-Free Massive MIMO‘ – has been published in IEEE Transactions on Communications.

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Mark-Jackson
By Mark Jackson
Mark is a professional technology writer, IT consultant and computer engineer from Dorset (England), he also founded ISPreview in 1999 and enjoys analysing the latest telecoms and broadband developments. Find me on X (Twitter), Mastodon, Facebook and .
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