About the Project
This research project will investigate how to learn from the behaviour of the radio channel in different parts of the network using big data from channel behaviour experienced by existing user equipment to build an evolving database of behaviour changing with time. It will then use this big data of channel behaviour and artificial intelligence to predict the channel behaviour that would be experienced by new user terminals admitted to the network to set the Radio Access Network’s (RAN) and user equipment’s (UE) radio transmission parameters. A model of the radio environment will be built and used to interact with a Mobile Edge Cloud Virtual Network Function that will hold the big data database and the artificial intelligence algorithms to deduce decisions on how to parameterise the RAN and UE in the call admission control process. Comparisons of the performance of the proposed admission control system will be compared with more conventional approaches to ascertain performance gains obtained using big data and artificial intelligence.
Communication Network students with a strong aptitude to software programming and IP networking are suitable
Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. Recently the UK Government made available the Doctoral Student Loans of up to £25,000 for UK and EU students and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.)