Information and energy are two fundamental notions in nature with critical impact on all aspects of life. All living and machine entities rely on both information and energy for their existence. Most, if not all, processes in life involve transforming, storing or transferring energy or information in one form or the other. Although these concepts are in harmony in nature, in traditional engineering design, information and energy are handled by two separate systems with limited interaction. In wireless communications, the relationship between information and energy is even more apparent as radio waves that carry information also transfer energy. Indeed, the first use of radio waves was for energy transfer rather than information transmission. However, despite the pioneering work of Tesla, who experimentally demonstrated wireless energy transfer (WET) in the late 19th century, modern wireless communication systems mainly focus on the information content of the radio-frequency (RF) radiation, neglecting the energy transported by the signal. This project is the first interdisciplinary initiative to promote innovation and technology transfer between academia and industry in the UK for one of the most challenging and most important problems in future communication networks: The simultaneous transfer of both energy and information. The aim of this project is to develop a new theoretical framework for the design and operation of next-generation networks with simultaneously wireless information and energy transfer (SWIFT) capabilities. The research efforts are interdisciplinary and bring together researchers with strong and complementary backgrounds in the domain of wireless communications such as electronics/microwave engineering, information theory, game theory, control theory, and communication theory to bridge the gap between theory and practice of future WET-based communication systems.

The recent advent of killer applications such as content distribution, cloud computing and Internet of things (IoT), all require for the underlying network to be able to understand specific service contexts. In this project we propose the Knowledge Centric Networking (KCN) paradigm, in which knowledge is positioned at the centre of the networking landscape. The objective is to enable in-network knowledge generation and distribution in order to develop necessary network control intelligence for handling complexity and uncertainty. In order to achieve this, specific algorithms and mechanisms/protocols will be developed for knowledge acquisition, processing, dissemination and organisation both within single and across homogeneous/heterogeneous administrative domains in the Internet. The project will investigate three styles of knowledge exchange based on Software Defined Networking (SDN) principles: Knowledge as a Tool (KaaT), Knowledge as a Service (KaaS) and Knowledge as a Cloud (KaaC). KaaT will enable intelligent network operations in dynamic network environments driven by knowledge gathered at different vantage points. We advocate a hierarchical knowledge framework in which knowledge and control functions are distributed at the right places within the network for fulfilling specific control tasks. In addition, we will invetigate knowledge sharing between different players in the Internet marketplace. This can be achieved either through explicit knowledge transfer from a knowledge provider to a knowledge consumer (KaaS), or based on open knowledge clouds where knowledge prosumers may publish or subscribe to information through an open but controlled knowledge ecosystem (KaaS). The proposed KCN architecture will be validated through two complementary use cases. KCN-driven content traffic offloading between heterogeneous radio access technologies for the future mobile Internet aims to achieve adaptive resource control by taking into account a wide variety of knowledge associated with content, users and network conditions. In addition, KCN-driven energy management targets cross-layer energy saving techniques at both the IP and the physical optical layer according to the derived knowledge and dynamically changing context information. The project provides direct contributions to the TI3 sub-challenges 1, 2, 3 and 4. First of all, the KCN-based knowledge ecosystem will equip the next generation Internet with necessary intelligence for handling complex requirements under dynamic conditions. Such an ecosystem, seamlessly coupled with the SDN architecture, will be able to gracefully support the ever increasing complexity and heterogeneity of future networked services and multitude of users. The two complementary use cases demonstrate how the proposed KCN framework will be instantiated in two different application domains, content traffic offloading in mobile/wireless access networks and energy efficiency in IP/optical transport networks. Use case 1 contributes to the 3rd sub-challenge, with knowledge-based content caching and traffic offloading techniques for the future content-oriented mobile Internet. Use case 2, on the other hand, contributes to the 2nd sub-challenge with intelligent energy saving mechanisms at both the IP and optical layer. Finally, with in-network knowledge inference and learning based on raw context information, the project also addresses the 4th sub-challenge of extracting understanding from data. In summary, context information captured during network/service operation will be used to derive systematic in-network knowledge and intelligence in order to deal adaptively with both complexity and uncertainty and enable near-optimal network operation.

The spectrum crunch is a global phenomenon, where wireless networks constrained by scarce spectrum resource cannot keep pace with the explosion in mobile broadband use, particularly at a time when smartphones and tablets are becoming even more prevalent and heavily used. Every new opportunity has to be maximally exploited to cope with this spectrum deficit and meet the demands of explosive broadband usage by pushing more data through existing spectrum. Massive multiple-input multiple-output (MIMO), an advanced antenna technology only developed in 2010 offers one such opportunity. Massive MIMO enables a sparse infrastructure network, whereby a single base station (BS) is powerful enough to eliminate inter-cell interference through highly directional beamforming, and hence avoid the need for any cell-to-cell coordination. Initial work, particularly the experiments in have demonstrated the feasibility of massive MIMO. However, there is still lack of insightful understanding of the fundamental limits of massive MIMO, and also there is a large gap in the performance evaluation of massive MIMO under ideal and non-ideal practical conditions. The aim of this project is to establish a unified theoretical framework for the fundamental limits of massive MIMO with various practical constraints, and develop sophisticated signal processing algorithms to realize the concept of massive MIMO in realistic environments. The novelty of this project lies in the fact that advanced mathematical tools, such as random matrix theory and stochastic geometry, will be used to capture the dynamic nature of multi-user wireless channels. Sophisticated signal processing methods, such as game theoretic algorithms and compressed sensing, will be applied to massive MIMO in order to combat the practical constraints, such as frequency selective channel fading and limited channel feedback.

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.

Information and energy are two fundamental notions in nature with critical impact on all aspects of life. All living and machine entities rely on both information and energy for their existence. Most, if not all, processes in life involve transforming, storing or transferring energy or information in one form or the other. Although these concepts are in harmony in nature, in traditional engineering design, information and energy are handled by two separate systems with limited interaction. In wireless communications, the relationship between information and energy is even more apparent as radio waves that carry information also transfer energy. Indeed, the first use of radio waves was for energy transfer rather than information transmission. However, despite the pioneering work of Tesla, who experimentally demonstrated wireless energy transfer (WET) in the late 19th century, modern wireless communication systems mainly focus on the information content of the radio-frequency (RF) radiation, neglecting the energy transported by the signal. This project is the first interdisciplinary initiative to promote innovation and technology transfer between academia and industry in the UK for one of the most challenging and most important problems in future communication networks: The simultaneous transfer of both energy and information. The aim of this project is to develop a new theoretical framework for the design and operation of next-generation networks with simultaneously wireless information and energy transfer (SWIFT) capabilities. The research efforts are interdisciplinary and bring together researchers with strong and complementary backgrounds in the domain of wireless communications such as electronics/microwave engineering, information theory, game theory, control theory, and communication theory to bridge the gap between theory and practice of future WET-based communication systems.