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Details of Grant 

EPSRC Reference: EP/Y000315/1
Title: Integrated Waveform and Intelligence (IWAI): Physical Layer Solutions to Sustainable 6G
Principal Investigator: Xu, Dr T
Other Investigators:
Researcher Co-Investigators:
Project Partners:
BT Rinicom Ltd UCL
Department: Sch of Engineering
Organisation: Newcastle University
Scheme: New Investigator Award
Starts: 01 March 2024 Ends: 28 February 2027 Value (£): 376,856
EPSRC Research Topic Classifications:
Artificial Intelligence Digital Signal Processing
RF & Microwave Technology
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
03 Jul 2023 EPSRC ICT Prioritisation Panel July 2023 Announced
Summary on Grant Application Form
Communications and information networks are ubiquitous in our daily life, and information and communications technology (ICT) is estimated to contribute 1.8%-2.8% of carbon emissions. The successful deployment of 5G has revealed that the total power consumption for a 5G communication system is much higher than that in 4G due to more densely placed base stations in 5G. A recent study also revealed that a potential 6G system would consume nearly 50 times higher power than a 5G system due to a larger number of antennas, a wider spectral bandwidth occupation, and a denser base station deployment strategy. 5G techniques have already been standardized and deployed in real life without the priority on net-zero sustainability. Therefore, to lead the sustainability innovations for next generation net-zero communications, we should reshape the physical layer techniques for 6G.

Improving energy efficiency has become the priority worldwide and has been identified as a key technology enabler for next generation 6G systems, and a number of industries and research institutes are chasing for net zero sustainable technology to achieve the objectives of cutting energy usage and carbon emission. This project aims for underpinning research in sustainable communication systems, which aligns with the UK government's top priority and ambitions on net zero in Wireless Infrastructure Strategy: a vision for 2030 (Source: GOV.UK).

Power consumption for a communication system is directly linked to physical components such as physical hardware and physical signals. Hardware upgrade via advanced manufacturing can cut power consumption but with limited contributions in 6G when more base stations are required to serve a given area. Therefore, a fundamental breakthrough in energy efficient physical signal design, more precisely waveform design, is timely and specially positioned to achieve net-zero goals in 6G.

A number of advancements have been achieved since 1924 when Harry Nyquist developed the foundation of today's digital communication signals. However, the existing waveform design in communication systems faces a number of fundamental challenges (a) Existing energy efficient air interface waveform designs are limited by the Mazo limit, which can only save power by up to 20% without any performance loss. However, the 20% power saving is no longer sufficient and the 20% is achievable at the cost of sophisticated and energy consuming signal processing. (b) Mathematically derived waveforms are limited by known mathematical models and are unlikely to be the optimal. (c) Machine learning can assist signals to have better performance but machine learning algorithms require lots of processing power. (d) Existing signal waveforms and AI models are commonly deployed using high energy consuming hardware because powerful computing resources are needed. To address the above challenges, an ambitious program is proposed including i) fundamental explorations of new waveforms beyond the conventional 20% power saving limit, ii) co-design of waveform and artificial intelligence to derive advanced waveform formats and cut the complexity of AI models, iii) low-cost hardware proof of concept with power saving validations.

The fundamental research breakthrough in the signal waveform design with intelligence will have impacts on researchers' work across many areas and fields, from circuit design to new communication systems, artificial intelligence algorithms, sensors and sensor networks, green communication techniques, advanced signal processing, biomedical signals, and other areas.

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