IDCoM Research Projects

Research Projects at the Institute for Digital Communications (IDCoM). You can search keywords within Project Titles.

We also have a number of Digital Communications PhD opportunities for postgraduate students looking to join the School.

Search keywords within Research Project titles
Project Title Principal Supervisorsort descending Project Summary
A systematic study of physical layer network coding: From Information-Theoretic Understanding to Practical DSP Algorithm Design

Dr Tharmalingam Ratnarajah

High spectral efficiency is the holy grail of wireless networks due to the well-known scarcity of radio spectrum. While up to recently there seemed to be no way out of the apparent end of the road in spectral efficiency growth, the emerging approach of Network Coding has cast new light in the spectral efficiency prospects of wireless networks [1]. Initial results have demonstrated that the use of network coding increases the spectral efficiency up to 50% [2, 3]. Such a significant performance gain is crucial for many important bandwidth-hungry applications such as broadband cellular systems, wireless sensor networks, underwater communication scenarios, etc.

HARP: High capacity network Architecture with Remote radio heads & Parasitic antenna arrays

Dr Tharmalingam Ratnarajah

To bring distributed multi-antenna wireless access to reality by combining two powerful emerging technologies:

radio remote heads (RRHs), which allow for widely geographically distributed access via radio-over-fibre connections to a central base station; and electronically steerable passive array radiators – ESPARs, which provide multi-antenna-like functionality with a single active RF chain only
Sensor Signal Processing

Professor Bernie Mulgrew

The fundamental challenges for signal processing are: how best to sense; how to distribute the processing and communication of the data within the network to maximize performance and minimize cost; how to analyze it to extract the salient information.

GREENNET An early stage training network in enabling technologies for GREEN radio

Professor Harald Haas

Greenet is an Initial Training Network (ITN) Marie Curie project that is focused on the analysis, design, and optimization of energy efficient wireless communication systems and networks.

Optical Free-Space Backhaul and Power for Energy Autonomous Small Cells

Professor Harald Haas

The central aim of the project is the design of a novel simple structure for a communication base station. Its operation will be based on off-the-shelf optical components such as white LEDs, laser-diodes and photo-diodes.

Tackling the looming spectrum crisis in Wireless Communication

Professor Harald Haas

The proposed work in this EPSRC Fellowship is aimed at providing radical new solutions to this fundamental and far reaching challenge. A key pillar of the proposed work is the extension of the RF spectrum to include the infrared as well as the visible light spectra. The recent advancements in light emitting diode (LED) device technology now seems to let the vision of using light for high speed wireless communications become a reality.

Robust Repeatable Respiratory Monitoring in EIT

Professor Hugh McCann

The project aims at developing a new electrical impedance tomography (EIT) device for medical use. This device, called ReMEIT, should enable 3D absolute conductivity image reconstruction. To achieve this goal the project intends to capture the exact positions of the measuring electrodes and the exact thoracic shape using an optical shape capture device. These are absolutely novel approaches in EIT imaging that, if successful, could represent an immense progress in EIT research and a big step towards reliable clinical use of this technology. The project partners not only plan to develop the device but they also propose a strategy for its validation under invivo conditions. At first, healthy volunteers with no history of lung disease will be examined by ReMEIT and, later, the EIT device will be applied in critically ill patients suffering from various pulmonary diseases. In the former case, reference data will be obtained by magnetic resonance imaging (MRI), in the latter one, routine chest X-ray, computed tomography (CT)and MRI data will be utilised.

UDRC: University Defence Research Collaboration in Signal Processing

Prof Mike Davies

Signal Processing is fundamental to the capability of all modern sensor weapon systems and the Defence Technology Strategy identified the development and application of signal processing techniques as high priority technical challenges within the MOD research agenda.

The UDRC is a leading partnership between industry, defence and is academia led and focuses on sensor signal processing for defence.

MacSeNet: Machine Sensing Training Network

Professor Mike Davies

The aim of this Innovative Training Network is to train a new generation of creative, entrepreneurial and innovative early stage researchers (ESRs) in the research area of measurement and estimation of signals using knowledge or data about the underlying structure.

Signal Processing for a Networked Battlespace

Professor Mike Davies

This research is carried out under the Unversity Defence Research Collaboration (UDRC) funded by the MOD and EPSRC.

The UDRC is a collaborative research project with the work being carried out by two Consortia. Edinburgh Consortium is made of the University of Edinburgh, Heriot-Watt University and The Queen's University of Belfast. LSSCN Consortium is made up of Loughborough University, University of Surrey, University of Strathclyde, Cardiff University and Newcastle University.

 

Pages

Subscribe to IDCoM Research Projects