The terahertz (THz) frequency region within the electromagnetic spectrum, covers a frequency range of about one hundred times that currently occupied by all radio, television, cellular radio, Wi-Fi, radar and other users and has proven and potential applications ranging from molecular spectroscopy through to communications, high resolution imaging (e.g. in the medical and pharmaceutical sectors) and security screening. Yet, the underpinning technology for the generation and detection of radiation in this spectral range remains severely limited, being based principally on Ti:sapphire (femtosecond) pulsed laser and photoconductive detector technology, the THz equivalent of the spark transmitter and coherer receiver for radio signals. The THz frequency range therefore does not benefit from the coherent techniques routinely used at microwave/optical frequencies. Our programme grant will address this. We have recently demonstrated optical communications technology-based techniques for the generation of high spectral purity continuous wave THz signals at UCL, together with state-of-the-art THz quantum cascade laser (QCL) technology at Cambridge/Leeds. We will bring together these internationally-leading researchers to create coherent systems across the entire THz spectrum. These will be exploited both for fundamental science (e.g. the study of nanostructured and mesoscopic electron systems) and for applications including short-range high-data-rate wireless communications, information processing, materials detection and high resolution imaging in three dimensions.

Artificial intelligence (AI) is on the verge of widespread deployment in ways that will impact our everyday lives. It might do so in the form of self-driving cars or of navigation systems optimising routes on the basis of real-time traffic information. It might do so through smart homes, in which usage of high-power devices is timed intelligently based on real- time forecasts of renewable generation. It might do so by automatically coordinating emergency vehicles in the event of a major incident, natural or man-made, or by coordinating swarms of small robots collectively engaged in some task, such as search-and-rescue. Much of the research on AI to date has focused on optimising the performance of a single agent carrying out a single well-specified task. There has been little work so far on emergent properties of systems in which large numbers of such agents are deployed, and the resulting interactions. Such interactions could end up disturbing the environments for which the agents have been optimised. For instance, if a large number of self-driving cars simultaneously choose the same route based on real-time information, it could overload roads on that route. If a large number of smart homes simultaneously switch devices on in response to an increase in wind energy generation, it could destabilise the power grid. If a large number of stock-trading algorithmic agents respond similarly to new information, it could destabilise financial markets. Thus, the emergent effects of interactions between autonomous agents inevitably modify their operating environment, raising significant concerns about the predictability and robustness of critical infrastructure networks. At the same time, they offer the prospect of optimising distributed AI systems to take advantage of cooperation, information sharing, and collective learning. The key future challenge is therefore to design distributed systems of interacting AIs that can exploit synergies in collective behaviour, while being resilient to unwanted emergent effects. Biological evolution has addressed many such challenges, with social insects such as ants and bees being an example of highly complex and well-adapted responses emerging at the colony level from the actions of very simple individual agents! The goal of this project is to develop the mathematical foundations for understanding and exploiting the emergent features of complex systems composed of relatively simple agents. While there has already been considerable research on such problems, the novelty of this project is in the use of information theory to study fundamental mathematical limits on learning and optimisation in such systems. Information theory is a branch of mathematics that is ideally suited to address such questions. Insights from this study will be used to inform the development of new algorithms for artificial agents operating in environments composed of large numbers of interacting agents. The project will bring together mathematicians working in information theory, network science and complex systems with engineers and computer scientists working on machine learning, AI and robotics. The aim goal is to translate theoretical insights into algorithms that are deployed onreal world applications real systems; lessons learned from deploying and testing the algorithms in interacting systems will be used to refine models and algorithms in a virtuous circle.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

We are living through a revolution, as electronic communications become ever more ubiquitous in our daily lives. The use of mobile and smart phone technology is becoming increasingly universal, with applications beyond voice communications including access to social and business data, entertainment through live and more immersive video streaming and distributed processing and storage of information through high performance data centres and the cloud. All of this needs to be achieved with high levels of reliability, flexibility and at low cost, and solutions need to integrate developments in theoretical algorithms, optimization of software and ongoing advances in hardware performance. These trends will continue to shape our future. By 2020 it is predicted that the number of network-connected devices will reach 1000 times the world's population: there will be 7 trillion connected devices for 7 billion people. This will result in 1.3 zettabytes of global internet traffic by 2016 (with over 80% of this being due to video), requiring a 27% increase in energy consumption by telecommunications networks. The UK's excellence in communications has been a focal point for inward investment for many years - already this sector has a value of £82Bn a year to the UK economy (~5.7% GDP). However this strength is threatened by an age imbalance in the workforce and a shortage of highly skilled researchers. Our CDT will bridge this skills gap, by training the next generation of researchers, who can ensure that the UK remains at the heart of the worldwide communications industry, providing a much needed growth dividend for our economy. It will be guided by the commercial imperatives from our industry partners, and motivated by application drivers in future cities, transport, e-health, homeland security and entertainment. The expansion of the UK internet business is fuelled by innovative product development in optical transport mechanisms, wireless enabled technologies and efficient data representations. It is thus essential that communications practitioners of the future have an overall system perspective, bridging the gaps between hardware and software, wireless and wired communications, and application drivers and network constraints. While communications technology is the enabler, it is humans that are the producers, consumers and beneficiaries in terms of its broader applications. Our programme will thus focus on the challenges within and the interactions between the key domains of People, Power and Performance. Over three cohorts, the new CDT will build on Bristol's core expertise in Efficient Systems and Enabling Technologies to engineer novel solutions, offering enhanced performance, lower cost and reduced environmental impact. We will train our students in the mathematical fundamentals which underpin modern communication systems and deliver both human and technological solutions for the communication systems landscape of the future. In summary, Future Communications 2 will produce a new type of PhD graduate: one who is intellectually leading, creative, mathematically rigorous and who understands the commercial implications of his or her work - people who are the future technical leaders in the sector.

Wireless communications has become a pervasive technology that we use throughout our lives. Across society, there is a move away from using the internet on desktop computers and towards smartphones, tablets and laptops. Consequently, the amount of wireless data transmission to support our online activities is rapidly increasing. There is also significant growth in automatic data sharing and collection from many types of sensors, meters and embedded computers, sometimes referred to as machine-to-machine (M2M) communications. This continuing growth in mobile data is a significant problem for network operators. In order to meet this enormous traffic growth challenge, operators are considering a number of potential solutions with three leading concepts: 1. increasing the availability of radio spectrum; 2. deploying heterogeneous and small cell networks; and 3. separating control and traffic data for enhanced network management. This project will address the expected capacity crunch by focusing on the RF bottleneck in future heterogeneous wireless networks through researching and developing miniature, integrated, reconfigurable and tuneable, multiband radios to enable 'spectrum agile' radio access and concurrent multiband operation. Research will address the radio system agility across the microwave spectrum bands from 450 to 6000 MHz. The project will embrace the co-design of antennas, amplifiers, filters and digitisers to achieve spectrum and energy efficient frequency agile radio systems. The project consists of five major research areas: 1. Tuneable Antennas and Filters - Research will focus on reconfigurable and tuneable antennas with integrated filters to achieve frequency selectivity and concurrent multiband operation. 2. Transmit Amplifiers - Research on transmit amplifiers for base stations and handsets will focus on methods to achieve re-tuneable, linear, wideband, power efficient and concurrent multiband operation. 3. Receiver Interference Mitigation - Simple and efficient solutions to reduce the effects of unwanted signal suppression caused by RF blockers in the multiband RF receiver chain will be sought. 4. Multiband A/D Conversion & PAPR Reduction - Research will focus on developing concurrent multiband ADC techniques at the receiver and the design of signal sets with significantly reduced peak-to-average-power ratio (PAPR). 5. Testbed Demonstration: Themes 1-4 will lead to the evaluation and demonstration of solutions using a hardware-in-the-loop RF testbed. By researching a frequency agile, concurrent multiband radio technology FARAD will significantly contribute to the growth of future radio access networks and the use of new spectrum bands in an efficient way. The techniques and algorithms developed in this project will enable far reaching capabilities in wireless networks for the next 20 to 30 years helping to solve the anticipated capacity crunch while establishing a new paradigm in radio transceiver design.