Revolutionary Solutions Addressing the Growing Impact of ‘Internet of Things’ on Mobile Networks
University of Leicester computer scientists have developed a novel technology to manage demands on mobile networks from multiple users using Terahertz frequencies.
As we see an explosion of devices joining the Internet of Things (IoT), this solution could improve speed and power consumption for users of mobile devices but could also help reap the benefits from the next generation of mobile technologies, 6G.
As the Internet of Things grows, more and more technology will compete to access those networks. State-of-the-art telecommunication technologies have been established for current applications in 5G. Still, with increasing demands of more users and devices, these systems demonstrate slower connections and costly energy consumption.
To deal with these challenges, a technique known as multicarrier-division duplex (MDD) has been recently proposed and studied, 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.
This project proposed a novel technology to optimize the assignment of subcarrier sets and the number of access point clusters and improve communication quality in different networks.
The team tested their technology in a simulation based on a real-world industrial setting, finding that it outperformed existing technologies. Lead Principal Investigator Professor Huiyu Zhou from the University of Leicester 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, more comprehensive, and with reduced power demands.
The team is now continuing to work on optimizing the proposed technologies and reducing the computational complexity of the technique. The source code of the proposed method has been published and shared with the world to promote the research.
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 response latency for future industrial applications of massive scale and varying demands. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 101017226.
