Renewable Energy, recycling and AI-driven Control for susTainable 6G networks (REACT)

REACT will develop and demonstrate a new approach to making future telecommunications networks more sustainable, energy-efficient and resilient. The project addresses the growing need to reduce the environmental impact of mobile networks while continuing to support increasing demand for high-quality connectivity.

Today’s mobile networks are mainly designed to meet peak demand. In busy urban and visitor locations, such as Blackpool Promenade and Winter Gardens, network traffic can rise sharply during weekends, public events and shows, while being much lower during quieter periods. This means that dense network infrastructure is needed to support busy times, but it can consume unnecessary energy when demand is low. REACT will address this challenge by using artificial intelligence to help the network understand and predict demand, then make better decisions about how resources should be used.

REACT will explore how solar panels and small-scale wind turbines can support battery-powered network nodes, helping reduce reliance on grid electricity. The project will develop AI-driven control methods that prioritise the use of renewable-powered nodes where possible, while managing the natural variability of solar and wind energy.

REACT will also address electronic waste through the development of modular, reconfigurable radio hardware. This will include a radio unit design with a tuneable 100 MHz passband front-end filter, enabling upgrades and improvements without replacing entire units. This supports a more circular approach to network equipment, reducing waste and extending equipment lifetimes.

The project will be validated using a high-fidelity network digital twin, extending the digital twin platform to include real user behaviour and renewable energy models. This will allow the consortium to test and optimise the system before live demonstrations.

REACT will deliver live demonstrations in Blackpool, digital twin demonstrations, modular radio hardware trials, technical reports, deployment know-how and a replicable reference architecture. The project will support mobile operators, neutral-host providers, local authorities and technology vendors in developing more sustainable connectivity infrastructure for the 6G era.

Orchestrated Mobile Network for Blackpool Intelligent Transport (ORBIT)

ORBIT is an 18-month collaborative project that will develop and demonstrate an advanced communications platform for Blackpool’s tramline and wider public transport network, including both trams and buses. The project will create a standalone non-public 5G network designed to support transport operations, passenger services and future intelligent applications in a live urban environment.

The project is motivated by the need for more reliable and controllable connectivity for public transport. In busy locations such as Blackpool, especially during seasonal peaks and major events, public mobile networks can experience heavy demand. Transport operators therefore need communications systems that can better support operational services, safety-related functions and digital passenger experience.

ORBIT will address this by integrating advanced wireless networking and edge computing into a single end-to-end system. The project will support use cases such as live CCTV streaming for incident management, delivery of passenger information and multimedia content to onboard screens, and communications for transport operations. 

A key feature of the project is its use of open and interoperable network technologies. Rather than relying on a closed single-vendor solution, ORBIT will bring together technologies from multiple partners and validate that they work effectively together in a transport setting. This will help demonstrate a flexible and scalable approach to future transport connectivity.

The project’s outputs will include live demonstrations, technical reports and public-facing dissemination materials, helping to inform future transport connectivity deployments in Blackpool and beyond.

O-RAN intelligent adaptive Load balancing and efficiency in highly Dense deployments

The ORLANDO project aims to develop intelligent, spectrum-efficient load balancing solutions for dense Open Radio Access Network (O-RAN) deployments. Benefiting from University of York’s partnerships made within previous successful DSIT-funded projects (YO-RAN and REACH), ORLANDO has access to a large data set of real users’ movement and traffic. The data set will be used to train a traffic prediction Machine Learning (ML) model and also fine tune a generative AI to generate synthetic data for new environments and unforeseen events. Two load balancing ML-based approaches will be investigated.

A centralised deep reinforcement learning-based xApp for small area load-balancing, and a scalable federated reinforcement learning-based architecture for larger RAN environments. The FRL architecture is expected to reduce the training energy consumption by 35%, in addition to its privacy preserving benefits. ORLANDO’s solutions will be tested on an Digital Twin like emulation environment (VIAVI’s AI-RSG), and trialed on York testbed and Blackpool winter gardens increasing its TRL from 2 to 5. 

YO-RAN (Yorkshire Open RAN) brings together two leading Yorkshire universities with a number of suppliers and network operators, several based in and around Yorkshire, to develop Open RAN components and a RIC for Neutral Host Networks – another development which allows the same infrastructure to be used by multiple operators, and also by private or enterprise-based networks. This requires in particular low-cost generic Radio Units with configurable multiband capabilities which are not currently available, and efficient fronthaul interfaces to connect them with suitable Distributed Units – all configurable via a RAN Intelligent Controller which can respond to the dynamic needs of all the network users. Open-RAN is a new approach for Radio Access Networks (RANs) – which consist of all the infrastructure including base stations and associated connections to allow a mobile phone to connect to the telecommunications network. It creates an open network allowing different suppliers to provide different components, including the Radio Units (RUs) at the base stations and the Distributed Units (DUs) which process radio signals, creating a more open and competitive supplier “ecosystem”. The RAN network is also virtualised so that different functions can be performed in different locations under the control of software called the RAN Intelligent Controller (RIC). 

ORAN-TWIN is funded by EPSRC CHEDDAR Hub TMF uplift, Federated Telecoms Hub 6G Research Partnership Funds (THRPF). The task for ORAN-TWIN project is to integrate advanced machine learning techniques into ORAN xApps for dynamic resource allocation and test time data augmentation.

We plan to simulate diverse network conditions to generate synthetic data, optimize resource allocation and ensure real-time performance adaptation. Leveraging digital twin, the xApps can be interacting with virtual environments to avoid hardware cost and search overhead in the physical systems. Digital twin helps to detect and diagnose potential issues, thereby improving physical systems reliability and efficiency.

Tourist hotspots drive significant volumes of mobile traffic, presenting a challenge to existing mobile technologies. The REACH project brings together an exciting group of partners to find new solutions to address this challenge by improving the delivery of data in High Density Demand (HDD) areas.

By developing new tools for an intelligent controller, the partners will enhance different aspects of data delivery. The project will deliver 3 distinct O-RAN (Open Radio Access Networks) HDD trials that will demonstrate the technology using realistic data.

Mobile Access North Yorkshire

DCMS funded Interdisciplinary 5G Testbed and Trials project providing 5G connectivity to uncovered areas of North Yorkshire.

• We designed and developed rapidly deployable terrestrial and aerial 5G networks for providing coverage for temporary events and disaster relief tasks. 

• Supported two main use cases mountain rescue and outdoor large social events.

• SDR and open-source SRS software allow the mobile network to adapt to future 3GPP releases