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Future Communications

The University of Edinburgh provides research-driven solutions to transform and future-proof organisations on their digital transformation journey.

Future Communications is a multi-disciplinary collaborative endeavour that spans various Schools at the University (Engineering, Informatics, Mathematics) and Hubs (The Bayes Centre, Edinburgh Futures Institute, EPCC). Future Communications is led and coordinated by The Institute for Imaging, Data and Communications (IDCOM).

The IDCOM is one of the United Kingdom’s leading research groups working in the field of communications. The Institute consistently takes part in major research projects funded in this area.

It actively participates in TITAN, the EPSRC-funded research hub led by the University of Cambridge. This project involves around 20 UK research groups investigating novel concepts in networks of networks for the next generation of communications systems.

It also contributes to the EPSRC-funded COG-MHEAR project led by Napier University, which is using fifth-generation (5G) wireless technology to develop advanced hearing aids.

Key areas of expertise

Communications Systems

  • Networks: Our researchers have significant expertise in a wide variety of communications network technologies including radio frequency, free-space optical and optical fibre communications systems.
  • Next Generation Wireless: We develop advanced concepts that will be used in future mobile communications standards. The institute possesses a number of software radio platforms, an advanced radio channel emulator and a well-equipped anechoic chamber.
  • Optical Comms: We are a leading research group on both free-space optical laser communications and visible light technologies. Our work is supported by an advanced optical communications lab providing state-of-the-art testing facilities.

Machine Learning

  • Bayesian Inference: IDCOM possesses significant expertise in the theory of Bayesian inference for signal processing. Our work also explores practical applications relevant to communications, such as position fixing of wireless terminals.
  • Deep Learning: Our institute has significant expertise on the theory and practice of deep learning neural networks. In communications, we are currently exploring the application of deep learning to a wide variety of practical problems to explore its benefits.
  • Data Analytics: We are exploring how machine learning can make sense of many different types of data, from audio, through communications and radar data to medical signal processing applications.

Signal and Image Processing

  • Tomography: We are expert in tomography techniques that use waves to measure the properties of physical systems. Current interests include the use of communications signals for sensing targets in future communications systems and novel applications to robots.
  • Computational Imaging: Many real-world problems in medical and electromagnetic domains involve very complex processing to understand the images that are generated. This work explores energy-efficient techniques that permit the maximum information to be extracted.

The Institute for Imaging, Data and Communications current leads two major new research initiatives:

SPADS - EPSRC and MoD Centre for Doctoral Training (CDT) in Sensing, Processing, and AI for Defence and Security

SPADS will train the next generation of defence scientists: engineers, computer scientists, and mathematicians, capable of leading developments in generation-after-next information and communication technologies that are poised to transform the world of defence and security along with broader civilian society. This will be addressed by developing interconnected technology and sensing modalities working across multiple sensing domains, leveraging advances in autonomy, embedded systems, and AI across both software/algorithms and hardware.

CHAI - EPSRC AI Hub for Causality in Healthcare AI with Real Data

Causal AI unearths causal insights, formalises treatment effects, assesses outcome likelihood, and estimates counterfactuals. Incorporating causal principles is critical for delivering the National AI Strategy to ensure AI is technically and clinically safe, transparent, fair, trustworthy, and explainable. The CHAI Hub will bring together academia, industry, healthcare, and policymakers to co-create next-generation causal AI solutions.

Find out more

Craig Sheridan

External Relations & Impact Manager SPADS CDT
Business Development Executive, School of Engineering