Research units A-Z

A University of Glasgow research initiative within the CHEDDAR Hub, focused on next-generation telecom systems, distributed cloud architectures, and Integrated Sensing and Communications (ISAC) technologies.

A research project led by the University of Glasgow, in collaboration with Tyndall National Institute, focused on developing low-loss, low-latency active intelligent reconfigurable surfaces (IRS) for 6G and Integrated Sensing and Communications (ISAC). The project advances dynamic control of signal phase and amplitude for next-generation mmWave and THz wireless systems.

A research project led by the University of Glasgow, focused on developing policies for green electronics such as Reconfigurable Intelligent Surfaces (RIS) for world wide implementation of futuristic green electronics for a more sustainable ecosystem.

This research focuses on the development of Transmissive Reconfigurable Intelligent Surfaces (TRIS) operating at millimetre-wave (mmWave) frequencies to enhance wireless channel conditions in next-generation communication systems. Unlike conventional reflective RIS, TRIS enables signal transmission through engineered metasurfaces, allowing dynamic control of wavefronts while maintaining compact and low-power operation.

The project investigates reconfigurable unit-cell architectures, beam shaping, and phase/amplitude control mechanisms to mitigate path loss, blockage, and penetration losses inherent to mmWave propagation. By improving signal coverage, spectral efficiency, and link reliability, TRIS offers a green and scalable solution for future 6G-enabled smart cities, indoor networks, and high-capacity wireless environments with minimal additional energy consumption.

This research explores the design and implementation of optically transparent metasurfaces integrated onto window glass to improve wireless signal quality while preserving optical transparency and aesthetic integrity. These metasurfaces are engineered using transparent conductive materials and low-profile patterns that allow visible light transmission while selectively manipulating radio-frequency signals.

The proposed solution aims to address signal attenuation caused by modern energy-efficient buildings, where coated or metallic glass significantly degrades indoor connectivity. By embedding transparent metasurfaces directly into architectural glass, the system enhances signal penetration, indoor coverage, and user experience without the need for additional active infrastructure. This approach supports sustainable building design, reduced network energy consumption, and seamless integration of wireless technologies into future smart and green ecosystems.

This research explores the use of Reconfigurable Intelligent Surfaces (RIS) to enable non-line-of-sight (NLOS) sensing of human vital signs, offering a transformative approach to contactless and privacy-preserving healthcare monitoring. By intelligently reconfiguring the wireless propagation environment, RIS can enhance weak physiological signal reflections caused by respiration, heartbeat, and micro-body movements, even when the subject is obstructed by walls or other obstacles.

Operating across sub-6 GHz and mmWave frequency bands, the proposed system leverages RIS-assisted beam steering, signal focusing, and multipath control to improve sensing accuracy, robustness, and coverage in complex indoor environments. This technology has the potential to revolutionise remote patient monitoring, elderly care, emergency response, and in-home health assessment, while reducing reliance on wearable devices and minimizing energy consumption, aligning with the vision of sustainable and intelligent healthcare ecosystems.

RFSensingGPT is an ongoing research project focused on advancing 6G network intelligence through the integration of AI-driven RF sensing and telecommunications knowledge systems. The project aims to develop a multi-modal framework that combines radar spectrogram analysis with retrieval-augmented generation to enable intelligent interpretation of RF signals alongside large-scale domain knowledge. The research investigates operation across multiple frequency bands, including XeThru, 24 GHz, and 77 GHz, with an emphasis on low-latency processing for real-time applications. Target use cases include security monitoring, contactless healthcare sensing, spectrum awareness, and autonomous network control, supporting the vision of integrated sensing and communications in future wireless systems.

This research investigates the integration of Reconfigurable Intelligent Surfaces (RIS) into Integrated Sensing and Communication (ISAC) frameworks within Open RAN architectures, with the goal of enabling secure and resilient 6G networks. The proposed architecture embeds an ISAC Service Model (ISAC SM) within the Near-Real-Time RAN Intelligent Controller (Near-RT RIC), allowing xApps to jointly monitor and control communication and localisation functions across the O-RAN stack, including O-CU, O-DU, and O-RU components.

By dynamically configuring the RIS, the system aims to shape the wireless propagation environment, enhancing signal quality for legitimate users while limiting information leakage toward potential eavesdroppers. The project is currently focused on architecture design, analytical modelling, and simulation-based evaluation, alongside incremental integration into software-defined Open RAN testbeds such as BubbleRAN. The research seeks to establish secure-by-design, programmable wireless environments with relevance to robotics, teleoperation, and critical digital infrastructure.

This ongoing research project focuses on the development of a mobile microwave sensing system for the detection of surface cracks and carbon composite materials in critical structures. The proposed sensor operates by transmitting and receiving microwave signals while moving across structural surfaces, enabling real-time identification of cracks, material discontinuities, and composite characteristics based on electromagnetic response variations.

The research investigates sensing principles, antenna design, signal processing, and material interaction models to distinguish between surface damage and carbon composite regions. The system is intended for non-destructive testing (NDT) applications in industrial environments, with a particular focus on aircraft structures and aerospace components, where early detection of cracks and material degradation is critical for safety and maintenance efficiency. The project aims to support automated inspection workflows and reduce reliance on manual inspection methods in safety-critical industries.

This ongoing project develops a radar-based contactless stethoscope for non-invasive cardiac monitoring, capturing micro-vibrations from heart valve activity and thoracic motion. Using millimetre-wave radar and advanced signal processing, the system aims to isolate heart sounds, explore extensions to respiration and blood-pressure sensing, and provide a privacy-preserving alternative to optical or wearable monitoring. Applications include continuous vital-sign monitoring in clinical, home-care, and emergency settings, supporting early detection of cardiovascular abnormalities without direct patient contact.