This project will combine multiple data sources based on Oxford City and its social and economic development requirements. The team comprises BT as lead partner, to provide advanced data analytics and visual software tools, plus access to a number of networked large-scale data sources. The academic research partner is the world-leading Oxford Internet Institute (OII), who will lead on novel graph and network visualisation analysis. The end user is Oxford City Council, who have expressed a keen interest in the project outputs; as the city faces a number of challenging constraints in the coming decade. Driven by economic growth, population increase, housing demand, and serious transport issues. The city must also balance intense demands from tourism, and social provision for its large student population. The project will aim to integrate a number of social, economic and transport related data streams in real-time to provide the city with a revolutionary geo-spatial viewpoint and perspective into its emerging challenges. This new capability will facilitate city planning, resource management, social-economic development, and reduced pollution/congestion from improved transport operations

We seek funding to address the problem of video compression on devices with limited processing resources. This is an issue for mobile platforms, where battery power and processing capabilities are limited, and for systems in which a video codec competes with other applications for processor resources. With the adoption of complex video coding standards (such as H.264/AVC) for consumer and mobile applications, the problem of computationally-efficient video coding is becoming increasingly important. It is vital to research and develop high quality video compression with controlled, low processor utilisation. This will make it possible to extend the battery life of mobile video devices (because a lower-power processor consumes less battery power) and to accommodate more software applications on a single processor.To date, the typical approach to the problem of limited processing resources is to reduce video frame rate and/or reduce compression quality in order to meet a computational constraint, leading to poor quality, jerky video images and unpredictable performance. This is unpleasant for the general consumer and unacceptable for specialist application such as remote surveillance and remote medical diagnosis. In contrast, our solution offers a way of managing video coding complexity, maintaining smooth video with good image quality.This proposal has two unique aspects. The first aspect is a novel method of reducing the complexity of video coding. The problem of evaluating and choosing coding modes is analysed and placed in a Bayesian framework. An adaptive algorithm maintains excellent video quality whilst offering a controllable reduction in computation, out-performing existing heuristic approaches. The second aspect is a system for controlling and managing coding complexity based on real-time measurements and targets. This enables a codec to maintain smooth, clear video images and to adapt to changes in scene content and available processing capability. We will develop and integrate these two concepts into a system that offers, for the first time, control of video codec complexity in an adaptive, analytic framework. The outcomes of this work will be of direct benefit to developers and integrators of next generation video-based platforms.The project will be led by Dr Iain Richardson, internationally recognised for his work on standards-based video coding. Dr Richardson and Dr Zhao (co-investigator) are experts in the field of video codec complexity management. Visiting researcher Professor Maja Bystrom of Boston University has already collaborated with the research team in developing the research tools that will form the basis of this project. BT Research (Multimedia Coding Analysis Group) will provide expert advice from an industry perspective.

Large-scale distributed systems, such as the Internet, broadband wireless at home and mobile phone networks, raise many challenges for the design and engineering of the underlying infrastructure. Such systems crucially depend on robust and efficient communication and coordination protocols that ensure that the overall system is self-organising, timely and energy-efficient, possibly in the presence of unreliable network services and malicious or uncooperative agents. New protocols for distributed coordination are being introduced to manage the limited resources. They increasingly often rely on randomisation, which plays an important role in achieving de-centralisation, and resource awareness, for example adapting to the power level. The combination of randomness and nondeterminism that arises from the scheduling of distributed components introduces complex behaviours that may be difficult to reason about. Assuring correctness, dependability and quality of service of such distributed systems is thus a non-trivial task that necessitates a rigorous approach, and methods for quantitative evaluation of such systems against properties such as ``the probability of battery level dropping below minimum within 5 seconds is guaranteed to be below 0.01 in all critical situations'', are needed. Theoretical foundations of such quantitative analysis have been proposed, with some implemented in software tools and evaluated through case studies. However, no tools and techniques can directly address real programming languages endowed with features such as random choice and timing delays.This proposal is to further develop the foundations for reasoning about probabilistic systems to enable quantitative analysis of real programming languages. The research will involve extending the successful quantitative probabilistic model checker PRISM (www.cs.bham.ac.uk/~dxp/prism/) via predicate abstraction, and develop additional enhancements to the PRISM toolkit in collaboration with the extensive user community. The resulting techniques will also be relevant for other domains in which probabilistic model checking has proved successful, e.g. performance analysis, planning and systems biology.

Cooperative diversity is a scheme which allows a cluster of wireless terminals to collaborate by relaying signals for one another, and thus improve the link with an access point for all of them. Several such schemes have been proposed over the past few years, and have shown in theory that they could result in a remarkable improvement in performance. However there has been little work on the practical problems likely to be encountered in implementing such a scheme, such as synchronisation of the transmissions from the nodes and, not least, how the relaying will actually be implemented. This project will investigate practical implementation using a scheme based on space-time block codes, which are a very simple and effective way of implementing diversity transmission over multiple transmitting antennas. It will first investigate the effect of synchronisation and channel estimation errors on such a system, and then investigate practical ways to overcome these problems, using, for example, iterative decoding and estimation techniques. In a cooperative diversity system the diversity is provided by exploiting multiple routes through a network of single-antenna terminals, rather than multiple antennas on a single terminal. The programme will also investigate a more general model of this approach, based on the concepts of network coding, which could provide more efficient cooperative diversity schemes in the future.

According to the Ofcom's Digital Dividend report in 2007, spectrum is limited only because they are seriously underutilised due to rigid and inefficient management. It was reported that over 90% of locations could have around 100MHz spectrum available for other services. These underutilised or unused spectrum holes, also known as white spaces, are mainly due to the interleaved spectrum for the digital TV band. Given the fact that the entire 3G spectrum is only 75MHz, this is an unacceptable wastage. At the same time, however, this gives golden opportunities for mobile operators, broadband service providers and users in the UK to improve the QoE for personal communications using cognitive transmission in the spectrum TV white spaces. In this context, BT is committed to exploiting the TV spectrum white spaces for providing wireless broadband access for homes in rural areas using cognitive radio (CR) technologies. According to BT, there are 2.75 million customers in rural areas, known as "not-spots" where, as ridiculous as it sounds, have no 3G coverage and Internet service is pretty much limited to dial-up access over residential or business telephone lines. In the "not-spots", the service is less than 2M bps but the TV spectrum white spaces, if utilised properly, can potentially cover more than 25% of the "not-spots" for improved services. The opportunity is that homes in a neighbourhood can share their antennas and signal processing capability to deliver much higher QoE using the spectrum white spaces at no extra cost. This project takes a novel perspective of enhancing the energy and spectrum efficiencies of wireless communications via user cooperation (e.g., multiple homes cooperation), which offers the possibility to improve the channel by sharing the resources between users. This exceptionally challenging objective has the potential to redefine the architecture of wireless networks, provide a novel system solution for extending the coverage and enhancing the QoE of broadband communications. In this project, the PI and BT (as the industrial partner) will join force to address the optimisation problem for cognitive cooperation. Our aim is to tackle the fundamental technical challenges specific to a cooperative MIMO channel. For instance, the required optimisation will need to take into account of individual users' requirements, constraints and fairness issues. Also, the proposed cooperative solution is also required to be robust to imperfect channel state information (CSI) and asynchronousity of the cooperating nodes, and be realised in a distributed manner. BT will be a key partner to provide invaluable inputs on the practical level to ensure that the project deliverables are exploitable. The final outcome of the proposed project will be the technologies for self-optimising cooperative antenna systems which can be used to provide broadband coverage for "not-spot" areas over wireless in the TV spectrum white spaces.