TY - GEN
T1 - AI-Enabled Optical Communication Networks for 6G Telecommunication and Beyond
AU - Priyanshu, Deepa
AU - Barnat, Shemseddine Ethani
AU - Raya, Nasreen Abu
AU - Mahboob, Shireen Banu
AU - Almugahwi, Ayeshah
AU - Alabdulraheem, Abeer Rafi
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The development of 5G to 6G wireless networks requires the use of infrastructure that is ultrareliable, capacitive, and low-latency communication. The 6G systems will most likely build on optical communication which has high bandwidth and scalability. Nevertheless, optical device and data heterogeneity, and large volumes of information generated by photonic transceivers has been a major challenge of real time monitoring, resource allocation, and network optimization. Artificial Intelligence (AI) provides the potential way out of such issues by providing predictive analytics, adaptive control, and intelligent decision-making. The current paper summarizes recent optical communication technologies in 6G, demonstrates the potential of AI to improve its performance, and suggests a new AIassisted architecture of optical fronthaul and transport networks. The suggested approach has lower latency, high energy efficiency, and high throughput levels in comparison to traditional systems through simulationbased evaluation. The findings stress that AI implementation together with the optical communication technologies will play a critical role in bringing the vision of 6G and beyond to reality.
AB - The development of 5G to 6G wireless networks requires the use of infrastructure that is ultrareliable, capacitive, and low-latency communication. The 6G systems will most likely build on optical communication which has high bandwidth and scalability. Nevertheless, optical device and data heterogeneity, and large volumes of information generated by photonic transceivers has been a major challenge of real time monitoring, resource allocation, and network optimization. Artificial Intelligence (AI) provides the potential way out of such issues by providing predictive analytics, adaptive control, and intelligent decision-making. The current paper summarizes recent optical communication technologies in 6G, demonstrates the potential of AI to improve its performance, and suggests a new AIassisted architecture of optical fronthaul and transport networks. The suggested approach has lower latency, high energy efficiency, and high throughput levels in comparison to traditional systems through simulationbased evaluation. The findings stress that AI implementation together with the optical communication technologies will play a critical role in bringing the vision of 6G and beyond to reality.
KW - 6G
KW - Artificial Intelligence
KW - Edge Computing
KW - Optical Networks
KW - Photonic Communication
UR - https://www.scopus.com/pages/publications/105035384570
U2 - 10.1109/OPTIMA67660.2025.11380339
DO - 10.1109/OPTIMA67660.2025.11380339
M3 - Conference contribution
AN - SCOPUS:105035384570
T3 - Proceedings of the 2025 Optical Communication, Photonics, Telecommunications, and Intelligent Machine Applications, OPTIMA 2025
SP - 228
EP - 233
BT - Proceedings of the 2025 Optical Communication, Photonics, Telecommunications, and Intelligent Machine Applications, OPTIMA 2025
A2 - Yusupov, Ibrokhimbek
A2 - Berdiyev, Alisher
A2 - Makhmudjanov, Sarvar
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 Optical Communication, Photonics, Telecommunications, and Intelligent Machine Applications, OPTIMA 2025
Y2 - 4 December 2025 through 5 December 2025
ER -