A detailed relevance analysis of enabling technologies for 6G architectures
|Author:||Pivoto, Diego Gabriel Soares1; Rezende, Tibério Tavares1; Facina, Michelle Soares Pereira2;|
1Instituto Nacional de Telecomunicações, Santa Rita do Sapucaí, Brazil
2Fundação Centro de Pesquisa e Desenvolvimento em Telecomunicações, Campinas, Brazil
3Faculty of Computing, Federal University of Uberlândia, Uberlândia, Brazil
4Instituto de Informática (INF), Universidade Federal de Goiás, Goiânia, Brazil
5Federal Institute of Goiás, Inhumas, Brazil
6Federal Institute Catarinense, Concórdia, Brazil
7Centre for Wireless Communications, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 10.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe20231017140440
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2023-10-17
As society evolves as a whole, new demands arise with increasingly demanding prerequisites, consequently requiring more significant effort to be met. Such demands cover emerging applications, such as remote surgeries in Smart Health use cases, whose latency and reliability network requirements cannot be met by current communication systems; or simply improving current applications with more challenging requirements to be achieved, such as increasing the transmission rate in a mobile network, offering Quality of Service (QoS), and consequently, better user experience. Therefore, enabling technologies must be chosen to design an appropriate 6G architecture to address such demands. However, the explosion of emerging applications focused on different scopes and requirements to be met makes choosing these enabling technologies extremely complex and unpredictable. Thus, this article aims to create a methodology for analyzing the relevance of enabling technologies and use it to design an optimal architecture capable of meeting the 6G demands. For this purpose, two methods named as Average (AVG) and Analytic Hierarchy Process (AHP) have been selected, whose objective is to determine the relevance of an enabler for the 6G architecture, taking into account different degrees of influencing variables for this analysis, such as adherence to a certain architectural model; popularity in the research area; degree of innovation; synergy with other enablers; and support for requirements. Each of these methods presents a particular result. In the case of the AVG method, the criteria and variables are evaluated independently, and the arithmetic mean is employed to combine the evaluations into a single measure of suitability. In contrast, the AHP method considers the relative importance of criteria and variables in order to classify an optimal set of enabling technologies capable of fulfilling the key roles to be performed by a 6G architecture, and consequently meeting the main 6G demands. Our evaluation provides a unique perspective on 6G enablers, identifying issues and fostering research for future mobile architectures. The results obtained also provide researchers with the necessary information to stay updated on emerging enabling technologies and their suitability for designing new optimized 6G architectures.
|Pages:||89644 - 89684|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Rede Nacional de Ensino e Pesquisa (RNP), with resources from Ministério da Ciência, Tecnologia e Inovações e Comunicações (MCTIC), under the Brazil 6G Project of the Radiocommunication Reference Center (Centro de Referência em Radiocomunicações—CRR) of the National Institute of Telecommunications (Instituto Nacional de Telecomunicações, Inatel), Brazil, under Grant 01245.010604/2020-14; and in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)—Finance Code 001.
© The Author(s) 2023. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/.