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.

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.

In this 'information age', computation, communication and massive information handling have become the bread and butter of modern society. Internet networks, the web, and popular peer-to-peer networks are all examples of the transition we are witnessing from local, centralised computers to massive distributed networks of relatively low-power individual resources. These are our first glimpses of the amorphous computers of the future. More generally, amorphous computers include any large-scale network of computational units or processes that are connected through a flexible and constantly changing network of interactions. These may be swarms of microscopic robots or large sensor-arrays that monitor climate or pollution. The critically important feature common to these kinds of self-organising distributed systems is that the desired computation emerges and is not explicitly preprogrammed.The transition to amorphous computing brings with it enormous potential as well as risk (such as the virus epidemics that plague the internet). To exploit the advantages and avoid the dangers of amorphous computing, fundamentally new ways of coping with complexity are needed. To do so we plan to develop appropriate mathematical models and tools, on the one hand, and to derive appropriate engineering principles inspired by successful systems, on the other.One of the unifying features of amorphous computers is their active network structure. Thus, a natural mathematical entity for their description is the graph: a structure with nodes (processors) and edges (connections). Since by their very nature, the network structure of amorphous computers is non-prescribed, the study of random graphs is especially promising. To extend the theory of random graphs to real-world applications, new mathematics needs to be developed, including new families of random graphs, new tools for simulating their growth and dynamics and new methods for analysing the dynamics that takes place on these graphs. A key part of this proposal is the development of these tools and their application to specific models of amorphous computers, and ultimately to real systems (such as P2P networks and sensor arrays).One of the challenges of amorphous computing is to find useful analogies that provide insight into the requirements, capabilities and limitations of the systems at hand. In this proposal, we will draw inspiration from biological systems and the powerful computation they perform. Computational aspects of biological functions are found in almost any task: from evolution, though development, to information processing, and are evident on every level of organisation, including macro-molecules (e.g., protein folding), cells (e.g., regulatory networks of proteins and genes) and higher (neural networks and nervous systems). Built of microscopic, noisy and relatively unreliable components, biological systems are surprisingly effective and efficient. Unlike human-engineered computers, they are also dynamic and highly adaptive machines. They are typically distributed and decentralised, with each component following a set of local rules based on its environment to determine its actions. It is the emergence of a functional and coherent whole from an ensemble of simple and unreliable elements that we would like to capture for our own engineering purposes.

Wireless mesh networks (WMN) represent a new networking technology involving wireless devices that are typically fixed at buildings and other infrastructure. These devices act as access points for wireless services such as the Internet. Importantly, the access points may directly connect to each other and forward data to a destination. This is typically an Internet gateway where communication is transferred from wireless to wires/cables. The relaying of data in a WMN causes problems for maintaining quality of service. It is important that data is scheduled sequentially for transfer between pairs of sending and receiving devices because processing within a device cannot occur in parallel. Consequently scheduling ensures that collisions between transmissions do not occur. It also allows data to be routed along paths so that objectives such as latency and delay of data are minimized while fairness between users is maximized. Our contribution will include eliciting the complexities of the underlying communication dynamics in mathematical terms. Collaboration with our project partner (BT plc) will ensure that all relevant engineering issues are incorporated. The research project specifically looks at the problem of creating schedules so that objectives are resolved. Two types of schedules are addressed: those for the user who wishes to transfer data to-and-from a particular access point and those needed to relay data to other access points in the WMN. These scheduling problems are computationally complex and require research based on mathematics and computer science. This will determine the existence of such schedules and their creation using advanced computational methods. The outcome of this research is of particular interest to our project partner who will examine the engineering implications of using the techniques developed in this project for future WMN deployments such as Wireless Cities initiatives.

This project will develop new mathematical and simulation models for traffic in wireless sensor networks. A range of traffic models will be developed / some will be specific to particular applications, while others will be more general in nature, capturing the behaviour of a variety of application types. Traffic information from existing projects will provide empirical input to our studies. Our traffic models will be used to assess existing wireless sensor network protocols in the light of scalability, quality of data, dependability of data, and other important performance aspects which are discussed below. Optimised and customised protocols will be developed, and some of these will be assessed in field trials.