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Dr Mark Leeson

Underwater Optical Wireless Communications (UOWC)

The use of optical signals underwater offers the prospect of higher bandwidths and data rates for underwater communications than the incumbent acoustic methods. However, UOWC systems also suffer from severe absorption and scattering introduced by the underwater channel. They may also be blocked by a myriad of obstructions under the water. So, there are potential projects looking at coding methods, modulation schemes and protocols for UOWC, and the use of non-line-of-sight (NLOS) UOWC. It would also be possible to investigate the application of machine learning at the receiver of UOWC systems.

Network Optimisation

In many problems in both communication engineering and more generally, we need to find the best route through a network or the best configuration for a network. Over the last few years, work with Chinese collaborators has been carried out to develop a novel approach to this problem. The method is inspired by the natural ripple-spreading phenomenon that occurs on a water surface, which turns out to be a powerful new naturally inspired approach. Several contributions to the field have been made but there is ample scope to further develop the method, particularly in terms of finding new engineering and other applications. Students who enjoy the application of mathematical models to real world problems can thus work on this fascinating area.

Wireless Body Area Network (WBAN) Systems

Following work to produce a realistic channel model for communicating with medical implants, research has moved to maximising the lifetime of wireless biomedical implant systems. This has entailed the investigation of relaying communication protocols and the choice of modulation and coding methods for the WBANs. We have developed mathematical models of quality of service (QoS) with the related subjective performance metrics. Work has also been extended the use of small mobile edge computing (C-MEC) servers. This transfers complexity, computation resources and energy consumption from user equipment to the C-MECs without long delays of cloud-based services. There is scope to further develop this work and investigate its optimisation.


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