In view of the rapid increase in demand for mobile data services, next generation wireless access networks will have to provide greatly increased capacity density, up to 10 Gbps per square kilometre. This will require a much larger density of very small, cheap and energy-efficient base stations, and will place increasing demand on the bandwidth and energy efficiency of the network, and especially the backhaul network. Recent work on network MIMO, or coordinated multipoint (CoMP) has shown that by ensuring base stations cooperate to serve users, especially those close to cell edge, rather than interferring with one another, inter-user interference can be effectively eliminated, greatly increasing the efficiency of the network, in terms of both spectrum and energy. However this tends to greatly increase the backhaul load. This work proposes a form of wireless network coding, called network coded modulation, as an alternative to conventional CoMP. This also enables base station cooperation, but instead of sending multiple separate information flows to each base station, flows are combined using network coding, which in principle allows cooperation with no increase in backhaul load compared to non-cooperative transmission, while gaining very similar advantages to CoMP in terms of bandwidth and energy efficiency. The objective of the proposed work is to establish the practical feasibility of this approach, and evaluate its benefits, as applied to next generation wireless access networks. To this end it will develop practical signalling schemes, network coordination and management protocols, and, with the help of industrial collaborators, will ensure compatibility with developing wireless standards.

This Centre for Doctoral training in Industrially Focused Mathematical Modelling will train the next generation of applied mathematicians to fill critical roles in industry and academia. Complex industrial problems can often be addressed, understood, and mitigated by applying modern quantitative methods. To effectively and efficiently apply these techniques requires talented mathematicians with well-practised problem-solving skills. They need to have a very strong grasp of the mathematical approaches that might need to be brought to bear, have a breadth of understanding of how to convert complex practical problems into relevant abstract mathematical forms, have knowledge and skills to solve the resulting mathematical problems efficiently and accurately, and have a wide experience of how to communicate and interact in a multidisciplinary environment. This CDT has been designed by academics in close collaboration with industrialists from many different sectors. Our 35 current CDT industrial partners cover the sectors of: consumer products (Sharp), defence (Selex, Thales), communications (BT, Vodafone), energy (Amec, BP, Camlin, Culham, DuPont, GE Energy, Infineum, Schlumberger x2, VerdErg), filtration (Pall Corp), finance (HSBC, Lloyds TSB), food and beverage (Nestle, Mondelez), healthcare (e-therapeutics, Lein Applied Diagnostics, Oxford Instruments, Siemens, Solitonik), manufacturing (Elkem, Saint Gobain), retail (dunnhumby), and software (Amazon, cd-adapco, IBM, NAG, NVIDIA), along with two consultancy companies (PA Consulting, Tessella) and we are in active discussion with other companies to grow our partner base. Our partners have five key roles: (i) they help guide and steer the centre by participating in an Industrial Engagement Committee, (ii) they deliver a substantial elements of the training and provide a broad exposure for the cohorts, (iii) they provide current challenges for our students to tackle for their doctoral research, iv) they give a very wide experience and perspective of possible applications and sectors thereby making the students highly flexible and extremely attractive to employers, and v) they provide significant funding for the CDT activities. Each cohort will learn how to apply appropriate mathematical techniques to a wide range of industrial problems in a highly interactive environment. In year one, the students will be trained in mathematical skills spanning continuum and discrete modelling, and scientific computing, closely integrated with practical applications and problem solving. The experience of addressing industrial problems and understanding their context will be further enhanced by periods where our partners will deliver a broad range of relevant material. Students will undertake two industrially focused mini-projects, one from an academic perspective and the other immersed in a partner organisation. Each student will then embark on their doctoral research project which will allow them to hone their skills and techniques while tackling a practical industrial challenge. The resulting doctoral students will be highly sought after; by industry for their flexible and quantitative abilities that will help them gain a competitive edge, and by universities to allow cutting-edge mathematical research to be motivated by practical problems and be readily exploitable.