User-Centric Multi-RATs Coordination for 5G Heterogeneous Ultra-Dense Networks

This column reviews the concept of user-centric access, which permits the network to tailor a “follow me” virtual cell for a user via multipoint coordination in a UDN environment. We further discuss the feasibility of extending such a virtual cell by considering tight integration of heterogeneous RATs exposed to the user, by taking the context information and instantaneous status of the user device into account. In particular, we conceive an edge/fog computing platform capable of acquiring and jointly processing information from multiple heterogeneous RATs and the users. Such a framework may have great potential to play key roles in 5G and beyond, in terms of realizing truly flexible radio access that can be customized for each individual user in the network.This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant no. 761586)

Potential Applicability of Distributed Ledger to Wireless Networking Technologies

In recent years, the rise of cryptocurrency has received enormous attention around the world. Since a centralized entity (e.g., a bank) is no longer needed for transactions in this currency platform, its potential impact on the financial sector in the future has been examined closely. Apart from the transaction platform itself, the driving technology behind cryptocurrency, namely blockchain, has also kindled huge research interest across different disciplines.This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant no. 761586)

Low complexity soft demapping for non-binary LDPC codes

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5GEN: A tool to generate 5G infrastructure graphs

This paper has been presented at : 2019 IEEE Conference on Standards for Communications and NetworkingOngoing research on 5G is looking on software platforms to evaluate new developments on 5G networks. Some 5G hardware is now starting to be available, but it is scarce and very limited, which makes validation and performance evaluation of 5G quite challenging. Simulation is the tool of choice for most of the cases, but this requires creating large descriptor files representing a 5G network. This brings forward the need for tools that facilitate the generation of 5G networks' topologies. In this paper we present 5GEN, a tool that automatically creates graphs representing 5G networks. With 5GEN, a researcher can just define the number of resources, and 5GEN will generate the nodes and edges that interconnect them across the infrastructure. The tool has been successfully used to test several 5G network scenarios within the EU 5G-CORAL project.Work was partially funded by EU H2020 5G-TRANSFORMER Project (grant no. 761536) and EU H2020 5G-CORAL Project (grant no. 761586).Work was partially funded by EU H2020 5G-TRANSFORMER Project (grant no. 761536) and EU H2020 5G-CORAL Project (grant no. 761586)

An Edge and Fog Computing Platform for Effective Deployment of 360 Video Applications

This paper has been presented at: Seventh International Workshop on Cloud Technologies and Energy Efficiency in Mobile Communication Networks (CLEEN 2019). How cloudy and green will mobile network and services be? 15 April 2019 - Marrakech, MoroccoIn press / En prensaImmersive video applications based on 360 video streaming require high-bandwidth, high-reliability and lowlatency 5G connectivity but also flexible, low-latency and costeffective computing deployment. This paper proposes a novel solution for decomposing and distributing the end-to-end 360 video streaming service across three computing tiers, namely cloud, edge and constrained fog, in order of proximity to the end user client. The streaming service is aided with an adaptive viewport technique. The proposed solution is based on the H2020 5G-CORAL system architecture using micro-services-based design and a unified orchestration and control across all three tiers based on Fog05. Performance evaluation of the proposed solution shows noticeable reduction in bandwidth consumption, energy consumption, and deployment costs, as compared to a solution where the streaming service is all delivered out of one computing location such as the Cloud.This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant num. 761586)

A baseline roadmap for advanced wireless research beyond 5G

This paper presents a baseline roadmap for the evolution of 5G new radio over the next decade. Three timescales are considered, namely short-term (2022-ish), medium-term (2025-ish), and long-term (2030-ish). The evolution of the target key performance indicators (KPIs) is first analyzed by accounting for forecasts on the emerging use cases and their requirements, together with assumptions on the pace of technology advancements. The baseline roadmap is derived next by capturing the top-10 and next the top-5 technology trends envisioned to bring significant added value at each timescale. Being intrinsically predictive, our proposed baseline roadmap cannot assert with certainty the values of the target KPIs and the shortlisting of the technology trends. It is, however, aimed at driving discussions and collecting feedback from the wireless research community for future tuning and refinement as the 5G evolution journey progresses.This research was funded by the European Union's Horizon 2020 research and innovation programme under grant number No 824994

Enhancing Edge robotics through the use of context information

Cloud robotics aims at endowing robot systems with powerful capabilities by leveraging the computing resources available in theCloud. To that end, the Cloud infrastructure consolidates servicesand information among the robots, enabling a degree of centralization which has the potential to improve operations. Despite beingvery promising, Cloud robotics presents two critical issues: (i) it isvery hard to control the network between the robots and the Cloud(e.g., long delays, high jitter), and (ii) local context information (e.g.,on the access network) is not available in the Cloud. This makeshard to achieve deterministic performance for robotics applications.Over the last few years, Edge computing has emerged as a trend toprovide services and computing capabilities directly in the accessnetwork. This is so because of the additional benefits enabled byEdge computing: (i) it is easier to control the network end-to-end,and (ii) local context information (e.g., about the wireless channel) can be made available for use by applications. The goal of this paperis to showcase, by means of real-life experimentation, the benefits ofresiding at the Edge for robotics applications, due to the possibilityof consuming context information locally available. In our experimentation, an application running in the Edge controls over a Wi-Filink the movement of a robot. Information related to the wirelesschannel is made available via a service at the Edge, which is thenconsumed by the application.Results show that a smoother drivingof the robot can be achieved when wireless quality information isconsidered as input of the movement control algorithm.This article has been partially supported by the EU H2020 5G-CORAL Project (grant no. 761586) and by the 5G-City project (grant no. TEC2016-76795-C6-3-R) funded by the Spanish Ministry of Economy and Competitiveness

On the integration of NFV and MEC technologies: architecture analysis and benefits for edge robotics

Forthcoming networks will need to accommodate a large variety of services over a common shared infrastructure. To achieve the necessary flexibility and cost savings, these networks will need to leverage two promising technologies: Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC). While the benefits of NFV and MEC have been largely studied as independent domains, the benefits of an harmonized system comprising these two technologies remains largely unexplored. In this article we first identify a set of reference use cases that would benefit from a joint use of MEC and NFV. Then, we analyze the current state-of-the-art on MEC and NFV integration and we identify several issues that prevent a seamless integration. Next, we consider a reference use case, namely Edge Robotics, to exemplify and characterize these issues in terms of the overall service life cycle: from the initial development, to deployment and termination.This work has been partially funded by the EU H2020 5G-TRANSFORMER Project (grant no. 761536), the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant no. 761586) and the EU H2020 5GROWTH Project (grant no. 856709)

A set of invariant and stable descriptors for 3D gray-levels objects

The description of 3D objects independently of their position and orientation, is an important and difficult problem in pattern analysis. In this paper, we deal with this problem by a pseudo-Fourier transform on the group of motions of the 3D Euclidean space, which we denote by M(3). This transform allows us to define 3D gray-levels object descriptors which are invariant and stable with respect to M(3). This method is applied to human bones automatic classification and description.La description d'objets tridimensionnels indépendamment de leur position et de leur orientation est un problème important et difficile de l'analyse de formes. Dans cet article, nous traitons ce problème à l'aide d'une pseudo-transformation de Fourier sur le groupe M(3) des déplacements de l'espace euclidien à trois dimensions. Celle-ci nous permet de définir des descripteurs de volumes à niveaux de gris stables et invariants par rapport à M(3). Cette méthode est appliquée à la classification et la description automatiques d'os humains