The pandemic caused by COVID-19 has shed light on the urgency of bridging the digital divide to guarantee equity in the fruition of different services by all citizens. The inability to access the digital world may be due to a lack of network infrastructure, which we refer to as service-delivery divide, or to the physical conditions, handicaps, age, or digital illiteracy of the citizens, that is mentioned as service-fruition divide. In this paper, we discuss the way how future sixth-generation (6G) systems can remedy actual limitations in the realization of a truly digital world. Hence, we introduce the key technologies for bridging the digital gap and show how they can work in two use cases of particular importance, namely eHealth and education, where digital inequalities have been dramatically augmented by the pandemic. Finally, considerations about the socio-economical impacts of future 6G solutions are drawn.

6G to Take the Digital Divide by Storm: Key Technologies and Trends to Bridge the Gap

Chiara Suraci;Sara Pizzi
;
Giuseppe Araniti
2022-01-01

Abstract

The pandemic caused by COVID-19 has shed light on the urgency of bridging the digital divide to guarantee equity in the fruition of different services by all citizens. The inability to access the digital world may be due to a lack of network infrastructure, which we refer to as service-delivery divide, or to the physical conditions, handicaps, age, or digital illiteracy of the citizens, that is mentioned as service-fruition divide. In this paper, we discuss the way how future sixth-generation (6G) systems can remedy actual limitations in the realization of a truly digital world. Hence, we introduce the key technologies for bridging the digital gap and show how they can work in two use cases of particular importance, namely eHealth and education, where digital inequalities have been dramatically augmented by the pandemic. Finally, considerations about the socio-economical impacts of future 6G solutions are drawn.
2022
6G, digital divide, NTNs, AI, XR, MEC, affective computing, BCI, D2D, use cases
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/133509
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