Securing elastic radio access networks

G networks have emerged as a promising solution for Mobile Network Operators (MNOs) to offer ultra-fast mobile broadband and ultra-low latency services with exceptional reliability for consumers. By leveraging softwarization, Software-Defined Networking (SDN) and Network Function Virtualization (NFV), MNOs can offset the high capital and operational expenditures incurred due the additional deployment of legacy equipment. […]

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Data driven energy efficient base station sleep control for 5G systems

The objective of this project is to develop a software system which can optimally control the base station sleep states in 5G networks to save energy. The 5G wireless networks are required to be green and yield very low carbon dioxide emissions. Compared with that of 4G wireless networks, the power efficiency of 5G is […]

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Intelligent Cyber-Physical Situational Awareness for Smart Infrastructures

The availability of big data in smart infrastructures have become a strategical asset for operators to understand the situation of the infrastructure and monitor potential threats. However, most of the data still have not circulated beyond traditional corporation and technological boundaries, which have limited the visibility that could have been provided by the abundant data. […]

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Transparent and Trustworthy Deep Feature Learning for Cyber-Physical System Security

The latest artificial intelligence (AI) technologies have effectively leveraged the wealth of data from cyber-physical systems (CPSs) to automate intelligent decisions. However, for safety-critical CPS like smart grids and smart cities, the conversion of massive data into actionable information by the AI must be not only effective but also reliable. To this end, this project […]

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Machine Learning and Data Mining Approaches for Smart Buildings

The goal of this project is to develop machine learning and data mining algorithms relying on non-intrusive common sensor data to estimate and predict smart buildings’ occupancy and activities. Efficient feedbacks are automatically supplied to the end user to involve occupants and increase their awareness about energy systems. This consists of generating reports helping the […]

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D2K+: Deep Learning of System Crash and Failure Reports for DevOps

The objective of this project is to develop techniques and tools that leverage artificial intelligence to automate the process of handling system crashes at Ericsson, one of the largest telecom and software companies in the world, and where the handling of crash reports (CRs) and continuous monitoring of key infrastructures tend to be particularly complex […]

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Self-Adaptive Penetration Tests with Deep-Reinforced Intelligent Agents

Penetration testing is a key security tactic, where defenders thinks like an attacker to predict the latter’s actions and develop effective defense. However, for large-scale cyber-physical infrastructures like the smart grid, traditional penetration tests on individual devices or networks are insufficient to exhaust all potential exploits or to reveal infrastructure-level vulnerabilities invisible to the local […]

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Edge-Twin based Framework for Real-Time AI Applications for Vehicular Scenarios

Edge computing is expected to play a transformative role for future AI applications in 5G networks by bringing cloud-style resource provisioning closer to the devices that have the data. Instead of running resource-intensive AI applications at the end devices, we can consolidate their execution at the edge, which brings many benefits, such as eliminating the […]

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Multi-agent reinforcement learning for distributed edge caching

There is an exponential increase in the network traffic worldwide due to the growth of social networks, multimedia sharing web services, streaming of video-on-demand (VoD) contents. However, the bandwidth isn’t growing at the same rate as the demand, resulting in a loss of Quality of Service (QoS) and Quality of Experience (QoE) for the users. […]

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Exploration of the cloud programming paradigm applied to IMS

For economical and simplification purpose Operators in the Telecom market are looking to move as much as possible of their infrastructure from traditional deployment to Cloud deployment. However Cloud deployment of IMS still need to be defined and developed. This project aims at bringing further the knowledge for such a deployment and helping guide future […]

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All Digital, Multi-Standard Highly Efficient Transmitter forMobile Communication Base Station Applications

A novel transmitter architecture which presents more power efficiency than that of the transmitters being used currently in mobile communication base stations is proposed in this research project. The result of this research fills the gap between the theoretical idea behind this transmitter structure and its practical usage in cellular network base stations. This transmitter […]

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