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Communication Sensing and Imaging Lab

University of Glasgow

University of Glasgow

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Sensing and Materials

ADVANCED SENSORS AND DEVICES

Tele - Point of Care (PoC) tools for food safety, agriculture/aquaculture, healthcare (prognostic and diagnostic). Onsite testing via mobile phone apps and data transfer for offsite analytics.

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SIGNAL PROCESSING FOR FUTURE WAVEFORMS

Performance estimation for the fusion of radar and communication signals from modelling to experimentation. With further device integration and demands to offer more services for customers or gather more information for mobile radio head intelligence, the integration of radar to fulfil both the communication and radar function simultaneously, however the choice of waveform and architecture is specific to the usage and the designed performance metrics. CSI can propose a study for task technology fit to design a waveform suited for the application and estimate performances and hardware requirements to reach set goals.

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WIRELESS CHANNEL CHARACTERIZATION AND MODELLING

Focus is on parametric stochastic channel modelling of small scale and large-scale variations in wireless propagation channels. Contrary to other approaches widely employed, such as measurement/site specific-, simulation (e.g., FDTD, ray tracing)-, or geometry-based that heavily rely on the specific wireless scenario setting (measurement or site specific-based) or fail to accurately model all features of multipath propagation such as multi-bounce scattering (geometry-based), we have been adopting a parametric stochastic modelling approach that can adapt to every propagation scenario, e.g., urban cellular, vehicle-vehicle, point-to-point mmwave communications. The inherent spatial, temporal and frequency variations are stochastically modelled following a duality principle, i.e., concepts from spatial variations modelling to be adopted in frequency variations modelling, etc. The applicability and limitations of all channel modelling approaches is comprehensively considered in terms of accuracy and complexity. One more advantage is that the adopted methodology can be readily adapted in the design of a wide range of wireless components and systems such as, multi-antenna systems, OFDM, CDMA receivers and physical layer security modules.

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ENERGY HARVESTING COMMUNICATIONS

With the expected exponential growth of this market, resulting from the increase of data rates with the launch of 5G networks, the energy consumption of wireless networks is expected to increase dramatically. Energy harvesting (EH) is a promising solution to combat the energy inefficiency problem and make wireless network sustainable. The main idea for EH communication is to generate energy from the sources which do not cause CO2 emissions, e.g., solar cells, RF waves and wind turbines. In contrast to regular power supply solutions where a fixed amount of power is available throughout the operation, EH communication solutions are time dependent and the energy availability is a stochastic process. The system design philosophy for the sustainable EH communication system requires time domain optimization of the system resources such that energy is available before it is required. Energy efficient radio resource allocation and EH based solutions go hand to hand to make a wireless network sustainable and maximize the revenues for the network operators. The focus of research is to develop and analyse resource allocation algorithms in wireless networks to reduce the on-grid power consumption in future networks.

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