Project description
Smarter, greener 6G through AI-driven mobility optimisation
As the race to 6G intensifies, next-generation networks are under pressure to deliver faster, fairer and more energy-efficient connectivity. Supported by the Marie Skłodowska-Curie Actions programme, the AI4_Mobility_in6G project aims to address this challenge by combining AI with reconfigurable intelligent surfaces to control how wireless signals propagate. The project’s goal is to improve how user devices, resource blocks and smart surfaces interact to maximise throughput and efficiency. For that reason, it will introduce intelligent user role switching and deep reinforcement learning techniques to enhance connectivity in low-mobility situations. Overall, the project aims at developing sustainable, high-speed connectivity for future smart cities.
Objective
The evolution of 6G wireless networks relies on advanced multiple-access technologies that improve efficiency and scalability. Reconfigurable Intelligent Surfaces (RIS) are set to transform 6G by enabling dynamic control of signal propagation channels. This project focuses on optimizing User Equipment (UE) pairings with Resource Blocks (RBs) and RISs in RIS-assisted Non-Orthogonal Multiple Access (NOMA) environments, exploring various configurations to maximize system throughput, fairness, and energy efficiency. By integrating active and passive beamforming, our approach not only enhances communication performance but also reduces the carbon footprint by minimizing the need for additional base stations through efficient frequency reuse. With Munster Technological University (MTU) affiliated with ADAPT Centre, and secondment at Dell Technologies, this research is strategically positioned for high-impact outcomes. The project introduces a novel technique for intelligent role switching in low mobility networks (LMNs), enabling dynamic shifts between near and far users to enhance connectivity time. The methodology incorporates optimization algorithms such as Simulated Annealing, Hill Climbing, Genetic Algorithms, and Random Walk for heuristic solutions. For LMNs, we will develop and evaluate models based on stochastic geometry and deep reinforcement learning (DRL) (asynchronous advantage actor-critic) to optimize the angle of reflection (AoR) for RIS elements. Four-month secondment at Dell, Ireland, is a key aspect where industry-grade validation will assess the performance of RO3 and refine the interplay between the edge-cloud continuum for the DRL. These models aim to address challenges in RIS-assisted networks, supporting seamless 6G connectivity in smart and sustainable cities. Ultimately, the research will advance green communications by optimizing network designs for energy-efficient infrastructure, aligning with EU goals for sustainable smarter cities.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology environmental engineering ecosystem-based management climatic change mitigation
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
- natural sciences mathematics pure mathematics geometry
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
T12 P928 Cork
Ireland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.