7,305 research outputs found
Results and achievements of the ALLIANCE Project: New network solutions for 5G and beyond
Leaving the current 4th generation of mobile communications behind, 5G will represent a disruptive paradigm shift integrating 5G Radio Access Networks (RANs), ultra-high-capacity access/metro/core optical networks, and intra-datacentre (DC) network and computational resources into a single converged 5G network infrastructure. The present paper overviews the main achievements obtained in the ALLIANCE project. This project ambitiously aims at architecting a converged 5G-enabled network infrastructure satisfying those needs to effectively realise the envisioned upcoming Digital Society. In particular, we present two networking solutions for 5G and beyond 5G (B5G), such as Software Defined Networking/Network Function Virtualisation (SDN/NFV) on top of an ultra-high-capacity spatially and spectrally flexible all-optical network infrastructure, and the clean-slate Recursive Inter-Network Architecture (RINA) over packet networks, including access, metro, core and DC segments. The common umbrella of all these solutions is the Knowledge-Defined Networking (KDN)-based orchestration layer which, by implementing Artificial Intelligence (AI) techniques, enables an optimal end-to-end service provisioning. Finally, the cross-layer manager of the ALLIANCE architecture includes two novel elements, namely the monitoring element providing network and user data in real time to the KDN, and the blockchain-based trust element in charge of exchanging reliable and confident information with external domains.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness under contract FEDER TEC2017-90034-C2 (ALLIANCE project) and by the Generalitat de Catalunya under contract 2017SGR-1037 and 2017SGR-605.Peer ReviewedPostprint (published version
AI Testing Framework for Next-G O-RAN Networks: Requirements, Design, and Research Opportunities
Openness and intelligence are two enabling features to be introduced in next
generation wireless networks, e.g. Beyond 5G and 6G, to support service
heterogeneity, open hardware, optimal resource utilization, and on-demand
service deployment. The open radio access network (O-RAN) is a promising RAN
architecture to achieve both openness and intelligence through virtualized
network elements and well-defined interfaces. While deploying artificial
intelligence (AI) models is becoming easier in O-RAN, one significant challenge
that has been long neglected is the comprehensive testing of their performance
in realistic environments. This article presents a general automated,
distributed and AI-enabled testing framework to test AI models deployed in
O-RAN in terms of their decision-making performance, vulnerability and
security. This framework adopts a master-actor architecture to manage a number
of end devices for distributed testing. More importantly, it leverages AI to
automatically and intelligently explore the decision space of AI models in
O-RAN. Both software simulation testing and software-defined radio hardware
testing are supported, enabling rapid proof of concept research and
experimental research on wireless research platforms.Comment: To be published in IEEE Wireless Communications Magazin
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