TY - JOUR
T1 - Digital Twin-Assisted OWC
T2 - Toward Smart and Autonomous 6G Networks
AU - Eldeeb, Hossien B.
AU - Naser, Shimaa
AU - Bariah, Lina
AU - Muhaidat, Sami
AU - Uysal, Murat
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - With the advancements of high-resolution cameras, highly sensitive photodetectors, and energy-efficient light-emittingdiodes, optical wireless communication (OWC) has emerged as key-enabling technology for 6G. Similarly, digital twin (DT) technology has recently been proposed to meet the diverse requirements of emerging applications and provide efficient optimization of the overall system resources by enabling self-sustaining and proactive online learning. Within DT, various technology disciplines, including big data, artificial intelligence, intelligent computing, communication, and security-aware technologies, are integrated to create a virtual replica that reflects the physical system. Motivated by this, this paper discusses DT and its role in the reliable and ubiquitous implementation of OWC networks. We first provide an overview of this emerging research area by offering insights into the key enabling technologies and potential applications in the context of smart-autonomous OWC networks. Subsequently, we provide recent advancements and design aspects related to DT-assisted OWC systems. Finally, future research directions and the impact of different system factors on the overall network performance are discussed. To the best of the authors' knowledge, this is the first in-depth review in the literature on the integration of DT with OWC networks.
AB - With the advancements of high-resolution cameras, highly sensitive photodetectors, and energy-efficient light-emittingdiodes, optical wireless communication (OWC) has emerged as key-enabling technology for 6G. Similarly, digital twin (DT) technology has recently been proposed to meet the diverse requirements of emerging applications and provide efficient optimization of the overall system resources by enabling self-sustaining and proactive online learning. Within DT, various technology disciplines, including big data, artificial intelligence, intelligent computing, communication, and security-aware technologies, are integrated to create a virtual replica that reflects the physical system. Motivated by this, this paper discusses DT and its role in the reliable and ubiquitous implementation of OWC networks. We first provide an overview of this emerging research area by offering insights into the key enabling technologies and potential applications in the context of smart-autonomous OWC networks. Subsequently, we provide recent advancements and design aspects related to DT-assisted OWC systems. Finally, future research directions and the impact of different system factors on the overall network performance are discussed. To the best of the authors' knowledge, this is the first in-depth review in the literature on the integration of DT with OWC networks.
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U2 - 10.1109/MNET.2024.3374370
DO - 10.1109/MNET.2024.3374370
M3 - Article
AN - SCOPUS:85187393275
SN - 0890-8044
VL - 38
SP - 153
EP - 162
JO - IEEE Network
JF - IEEE Network
IS - 6
ER -