Autonomous AI-driven cell-free 5G network architecture for highly dynamic and ultra-dense connectivity
The purpose of this research is to develop a mobile network that does not have fixed cellular boundaries. In conventional cellular networks, each user equipment (UE) is connected to the access point (AP) in only one of the many cells (except during handover). At a given time instance, the APs have different numbers of active UEs, causing inter-cell interference. Cellular networks are suboptimal from a channel capacity viewpoint because higher spectral efficiency (SE) (bit/s/Hz/user) can potentially be achieved by co-processing each signal at multiple APs.
In cell-free networks, there are many more geographically distributed APs that can use artificial intelligent techniques to self-organise themselves into Multiple Input Multiple Output (MIMO) groups to jointly serve a relatively smaller number of UEs. Cell-free Massive MIMO can potentially provide ten-fold improvements in Spectral Efficiency for the UEs over a corresponding cellular network with small cells.
The cabling and internal communication between APs is also a challenging issue in practical cell-free Massive MIMO deployments. A cost-efficient architecture is one that self-organise APs as both access points as well as nodes in a front haul network that reduces the requirement for cabling between Aps.
The majority of the project will be carried out using MATLAB, crafting different sections of code to explore different algorithmic options and the Python to incorporate solution on 5G Multiaccess Edge Computing cloud.
Studentships may be available depending on availability and research performance. Please enquire with Prof. John Cosmas for more details.
How to apply
If you are interested in applying for the above PhD topic please follow the steps below:
- Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
- Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
- Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.
This is a self funded topic
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. The UK Government is also offering Doctoral Student Loans for eligible 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%.