Emilio Calvanese Strinati

Bio: Emilio Calvanese Strinati is an academic researcher from University of Grenoble. The author has contributed to research in topics: Network packet & Cellular network. The author has an hindex of 20, co-authored 165 publications receiving 2456 citations. Previous affiliations of Emilio Calvanese Strinati include French Alternative Energies and Atomic Energy Commission & Alternatives.

6G: The Next Frontier: From Holographic Messaging to Artificial Intelligence Using Subterahertz and Visible Light Communication

Abstract: With its ability to provide a single platform enabling a variety of services, such as enhanced mobile broadband communications, virtual reality, automated driving, and the Internet of Things, 5G represents a breakthrough in the design of communication networks. Nevertheless, considering the increasing requests for new services and predicting the development of new technologies within a decade, it is already possible to envision the need to move beyond 5G and design a new architecture incorporating innovative technologies to satisfy new needs at both the individual and societal levels.

A Survey on MAC Strategies for Cognitive Radio Networks

Abstract: Dynamic spectrum policies combined with software defined radio are powerful means to improve the overall spectral efficiency allowing the development of new wireless services and technologies. Medium Access Control (MAC) protocols exploit sensing stimuli to build up a spectrum opportunity map (cognitive sensing). Available resources are scheduled (dynamic spectrum allocation), improving coexistence between users that belong to heterogeneous systems (dynamic spectrum sharing). Furthermore, MAC protocols may allow cognitive users to vacate selected channels when their quality becomes unacceptable (dynamic spectrum mobility). The contribution of this survey is threefold. First, we show the fundamental role of the MAC layer and identify its functionalities in a cognitive radio (CR) network. Second, a classification of cognitive MAC protocols is proposed. Third, advantages, drawbacks, and further design challenges of cognitive MAC protocols are discussed.

EARTH — Energy Aware Radio and Network Technologies

Abstract: EARTH is a major new European research project starting in 2010 with 15 partners from 10 countries. Its main technical objective is to achieve a reduction of the overall energy consumption of mobile broadband networks by 50%. In contrast to previous efforts, EARTH regards both network aspects and individual radio components from a holistic point of view. Considering that the signal strength strongly decreases with the distance to the base station, small cells are more energy efficient than large cells. EARTH will develop corresponding deployment strategies as well as management algorithms and protocols on the network level. On the component level, the project focuses on base station optimizations as power amplifiers consume the most energy in the system. A power efficient transceiver will be developed that adapts to changing traffic load for an energy efficient operation in mobile radio systems. With these results EARTH will reduce energy costs and carbon dioxide emissions and will thus enable a sustainable increase of mobile data rates.

The Fog Balancing: Load Distribution for Small Cell Cloud Computing

Abstract: In 5G future wireless networks, the (ultra)-dense deployment of radio access points is a key drive for satisfying the increase of traffic demand and improving perceived users' quality (Ultra)-dense deployment combined with capillary edge cloud, the fog, leads the way for optimization of users' Quality of Experience (QoE) and network performance In this paper, we focus on improving users' QoE by addressing the issue of load balancing in fog computing In this paper, we consider the challenging case of multiple users requiring computation offloading, where all requests should be processed by local computation clusters resources We propose a low complexity small cell clusters establishment and resources management customizable algorithm for fog clustering Our simulation results show that the proposed algorithm yields high users' satisfaction percentage of a minimum of 90% for up to 4 users per small cell, moderate power consumption, and/or high latency gain

Where, When, and How mmWave is Used in 5G and Beyond

Abstract: Wireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but instead an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes. The paper starts with 28 GHz outdoor backhauling for fixed wireless access and moving hotspots, which will be demonstrated at the PyeongChang winter Olympic games in 2018. The second deployment example is a 60 GHz unlicensed indoor access system at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC) to enable ultra-high speed content download with low latency. The third example is mmWave mesh network to be used as a micro Radio Access Network ({\\mu}-RAN), for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and Vehicular-to-Everything (V2X) communications system, which enables automated driving by exchanging High Definition (HD) dynamic map information between cars and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play important roles for a diverse set of applications that require both ultra-high data rate and low latency communications.

Bit-Interleaved Coded Modulation

Abstract: Zehavi (1992) showed that the performance of coded modulation over a Rayleigh fading channel can be improved by bit-wise interleaving the encoder output and by using an appropriate soft-decision metric as an input to a Viterbi decoder. The goal of this paper is to present in a comprehensive fashion the theory underlying bit-interleaved coded modulation, to provide tools for evaluating its performance, and to give guidelines for its design.

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Abstract: Technological evolution of mobile user equipment (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. A suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud. Nevertheless, this option introduces significant execution delay consisting of delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such a delay is inconvenient and makes the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling it to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: 1) decision on computation offloading; 2) allocation of computing resource within the MEC; and 3) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Abstract: Technological evolution of mobile user equipments (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. Suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud (CC). Nevertheless, this option introduces significant execution delay consisting in delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such delay is inconvenient and make the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: i) decision on computation offloading, ii) allocation of computing resource within the MEC, and iii) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

Abstract: Multi-access edge computing (MEC) is an emerging ecosystem, which aims at converging telecommunication and IT services, providing a cloud computing platform at the edge of the radio access network MEC offers storage and computational resources at the edge, reducing latency for mobile end users and utilizing more efficiently the mobile backhaul and core networks This paper introduces a survey on MEC and focuses on the fundamental key enabling technologies It elaborates MEC orchestration considering both individual services and a network of MEC platforms supporting mobility, bringing light into the different orchestration deployment options In addition, this paper analyzes the MEC reference architecture and main deployment scenarios, which offer multi-tenancy support for application developers, content providers, and third parties Finally, this paper overviews the current standardization activities and elaborates further on open research challenges