Air Interface Challenges and Solutions for future 6G Networks


Benoit Miscopein, Jean-Baptiste Doré, Emilio Calvanese Strinati, Dimitri Kténas, Sergio Barbarossa: Air Interface Challenges and Solutions for future 6G Networks. In: 1st 6G Wireless Summit, 2019.

Abstract

5G networks are expected to be deployed in 2020 and are considered as a global game changer from a technological, economic, societal and environmental perspective with very aggressive performance levels in terms of latency, energy efficiency, wireless broadband capacity, elasticity, etc. Many experts say that the next big step for cellular networks is not 5G but its cloudification that will support the explosion of radically new services and applications ranging from immersive five-sense media to ambient sensing intelligence and a pervasive introduction of artificial intelligence. In our vision, the next generation of wireless systems will transform the 5G service-oriented networks into user and machine ad-hoc dynamic (re)configuration of network slices. This will be enabled by software-defined end-to-end solutions from the core to the radio access network, including the air interface as well as the RF and antenna systems which are envisioned as one of the keys to meet the user/service requirements. Users and machines will be indeed able to dynamically (re)configure network slices thanks to intelligent personal edges. This paper presents our perspective of the 6G air interface and raise the concept of software defined artificial intelligence and air interface (SD-AI 2) as a framework of 6G air interface. This concept is an extension of the one initially proposed for 5G [1]. Instead of a global optimized air interface, we envisage to bring agility and flexibility to air interface with the help of artificial intelligence and learning techniques to improve efficiency. The paper describes the proposed context and highlights the technical challenges at different levels.

BibTeX (Download)

@inproceedings{miscopein:cea-01986524,
title = {Air Interface Challenges and Solutions for future 6G Networks},
author = {Benoit Miscopein and Jean-Baptiste Dor\'{e} and Emilio Calvanese Strinati and Dimitri Kt\'{e}nas and Sergio Barbarossa},
url = {https://hal-cea.archives-ouvertes.fr/cea-01986524},
year  = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
booktitle = {1st 6G Wireless Summit},
abstract = {5G networks are expected to be deployed in 2020 and are considered as a global game changer from a technological, economic, societal and environmental perspective with very aggressive performance levels in terms of latency, energy efficiency, wireless broadband capacity, elasticity, etc. Many experts say that the next big step for cellular networks is not 5G but its cloudification that will support the explosion of radically new services and applications ranging from immersive five-sense media to ambient sensing intelligence and a pervasive introduction of artificial intelligence. In our vision, the next generation of wireless systems will transform the 5G service-oriented networks into user and machine ad-hoc dynamic (re)configuration of network slices. This will be enabled by software-defined end-to-end solutions from the core to the radio access network, including the air interface as well as the RF and antenna systems which are envisioned as one of the keys to meet the user/service requirements. Users and machines will be indeed able to dynamically (re)configure network slices thanks to intelligent personal edges. This paper presents our perspective of the 6G air interface and raise the concept of software defined artificial intelligence and air interface (SD-AI 2) as a framework of 6G air interface. This concept is an extension of the one initially proposed for 5G [1]. Instead of a global optimized air interface, we envisage to bring agility and flexibility to air interface with the help of artificial intelligence and learning techniques to improve efficiency. The paper describes the proposed context and highlights the technical challenges at different levels.},
keywords = {6G, air interface, artificial intelligence, beyond 5G, mobile edge cloud},
pubstate = {published},
tppubtype = {inproceedings}
}