As the standardization of 5G wireless networks progresses, the research community has started focusing on what 6G will be. Motivated by the need of ensuring high data-rates, while at the same time saving spectrum, a major technology that has been proposed for 6G is the integration of communication and sensing services in the same infrastructure. This enables wireless networks to perceive the surrounding environments, triggering new services and leading to a more efficient use of resources. The INTEGRATE project focuses on the theoretical, algorithmic, and architectural foundations of integrated communication and sensing networks, developing the first open access network-level simulator for joint communication and sensing. To this end, a new implementation of wireless transceiver is proposed, which leverages the use of reconfigurable holographic surfaces and allows the integration of communication and sensing with remarkable performance while at the same time reducing the energy consumption. Specifically, INTEGRATE will: 1) Develop reconfigurable holographic surfaces capable of supporting joint communication and sensing tasks and that can be integrated in wireless transceivers with minimal cost and energy requirements. 2) Characterize the fundamental performance limits of integrated communication and sensing networks, developing an algorithmic framework and protocol suite to approach these limits. 3) Build the first open access software simulation platform for joint communication and sensing networks.

Telecommunications underpin many sectors of modern life and especially the growing digital economy. The rapid growth of the telecommunications transmission capacity along with the significant reduction of the cost per bit has enabled development of new technologies and business models which revolutionised everyday life. The telecommunications backbone is formed by fibre optic communications enabling transmission of vast amount of data between virtually any points on the Earth. Multiplication of the fibre optic communications transmission capacity in the past decades have been provided mostly by several technological breakthroughs, such as employment of Erbium-doped fibre amplifiers or coherent receivers. The next significant advancement providing a revolutionary shift in fibre optic communications could be employment of multi-band transmission utilising the whole bandwidth available in modern optical communication fibres. Multi-band optical communications have potential to five-fold the transmission capacity without need to deploy new transmission fibres thus significantly reducing the costs. However, the key challenge for employment of multi-band transmission is lack of suitable optical amplifiers able to operate in the wavelength bands of interest and across several bands simultaneously. This project, Interferometric and Multiband optical Parametric Amplifiers for Communications (IMPAC), will provide the key advances necessary for fibre optic parametric amplifiers (FOPA) to enable EDFA-equivalent signal amplification in all wavelength bands appealing for multi-band communications (O, E, S, C, L) and with bandwidth in excess of 100 nm, potentially up to 200 nm. In IMPAC I will: 1. Create a fully autonomous and robust polarisation-insensitive (PI) FOPA with high net gain >20dB and low polarisation-dependent gain <0.5dB across a record wide bandwidth >100nm. 2. Pioneer interferometric FOPAs rejecting unwanted FWM products to double available gain bandwidth or to 'eliminate' nonlinear crosstalk with suppression of ~20dB. 3. Significantly (by a factor of 10) reduce the signal noise attributed to the stimulated Brillouin scattering mitigation, whilst allowing for a wide FOPA gain bandwidth of at least ~100nm. 4. Pioneer a PI-FOPA with gain tuneable across O/E/S bands for signal and pump amplification, and consequently create the first-ever distributed PI-FOPA in SSMF. 5. Devise the 'next generation' PI-FOPA combining the project achievements in terms of gain bandwidth, low noise figure, rejection of unwanted FWM and SBS mitigation to facilitate operation across a bandwidth up to 200nm with performance superior to commercial EDFAs.

Mobile communication networks have evolved over past decade from systems providing voice and basic messaging service to an integral part of society, enabling a rich set of services from voice and video communications, internet access, banking, logistics, navigation and emergency services. A growing customer base with highly capable data centric devices has fuelled a demand for capacity in radio access networks (RAN). To meet this demand, research and development has delivered generations of radio access technologies, rolled out globally, with 4G enabling true mobile broadband experience in the UK from October 2012. The latest manifestation, 5G, being deployed globally following the completion of standardisation in 2018-2019. One of the key technological differences in 5G RAN compared to 4G RAN is native use of active antenna systems to deliver an unprecedented step change in the efficiency of use by base stations of limited spectrum resources. Active antenna systems (AAS, also known as Massive MIMO) benefit from progress in circuit and electronics technology and low cost computing power in baseband processors to provide independent control over the multiple antenna elements comprising a cellular antenna. Such finer level of control enables basestations to fine-tune transmissions to individual user conditions and to enhance the reception of transmissions by users. The net effect on user experience can be described as a perception of infinite capacity, with a user receiving the resources that their service requires and consequent enhanced responsiveness of services and applications. The challenge beyond the impressive first steps in AAS research and implementation is to be able to address emerging applications and services carrying different connectivity requirements in terms of latency, reliability, coverage and speed. Many of such new use cases including various machine-to-network communications, industrial automation and transportation, emergency and critical services will have to be provided using the same network infrastructure, including the base stations and antenna systems. No technology exploiting capabilities of AAS for such multi-service use cases exists to date since the primary driver in research and academia has been capacity and energy efficiency. A concept of 'network slicing' does not address this research challenge either since it does not consider digital signal processing and architectures of AAS. This research programme will explore and deliver a multi-service processing capability in AAS, capable of balancing reliability, coverage and overall network capacity. Specifically, we will investigate the feasibility and performance bounds of such multiservice RAN in delivering mixed types of services sustainably through a single physical infrastructure. We will identify fundamental trade-off factors between reliability and capacity achievable on physical layer of RAN with AAS, and design processing methods to effectively support user differentiation while maintaining network capacity. We will work with industry and academic stakeholders within standardisation bodies and industry to drive the identified solutions to practical realisation and shape further evolution of technology.

Organisations, small and large, increasingly rely upon cloud environments to supply their ICT needs because clouds provide a better incremental cost structure, resource elasticity and simpler management. This trend is set to continue as increasingly information collected from mobile devices and smart environments including homes, infrastructures and smart-cities is uploaded and processed in cloud environments. Services delivered to users are also deployed in the cloud as this provides better scaleability and in some cases permits migration closer to the point of access for reduced latency. Clouds are therefore an attractive target for organised and skilled cyber-attacks. They are also more vulnerable as they host environments from multiple tenant organisations with different interests and different risk aversion profiles. Yet clouds also offer opportunities for better protection both pro-actively and reactively in response to a persistent attack. This project aims to develop novel techniques for intelligent cloud protection by advancing the state of the art in system modelling at run time, attack scenarios based analysis, novel techniques for selecting countermeasures and remedial actions and novel techniques for re-perimeterisation of the cloud environment. The methodology adopted combines fundamental research on knowledge representation, probabilistic analysis and machine learning with empirical and experimental studies in an industrial test-bed environment. Additionally, the project also aims to achieve a better understanding of the business models and incentives involved in the relationships between cloud tenants and hosting organisations in the provision of security services based on measures of cost, risk and value and to propose new models that facilitate sharing of risk and exchange of security relevant information, which would in turn allow to simplify security management and provide better protection.

Programming classical computers has become a popular practice thanks to high-level programming languages and compilers which enable the running of high-level programs on different computing platforms. For critical applications, we now have verified compilation schemes and certified compilers which ensure the correctness of the compiled executions. This is done by reference to a mathematical model of the high-level code. In this project we will establish such a promising trajectory for quantum computing, taking into account the subtle features of quantum computers. This will be achieved by bringing together expertise in software testing and quantum simulation. The results of this research will lead to verified software for quantum computing applications and consequently, to wide-spread and effective exploitation of quantum computing.