Machine Learning and AI in Optical Communication Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".
Deadline for manuscript submissions: 20 April 2026 | Viewed by 21
Special Issue Editors
Interests: optical communication systems; high capacity coherent communication; secure optical communication; physical layer security; optical identification; constellation shaping; physical unclonable function; digital signal processing; steganography
2. M.B.I. srl, 57128 Pisa, Italy
Interests: all-optical signal processing; fiber-optic transmission systems; applications of photonic microwave techniques to radar and wireless communications; optical beamforming for 5G; photonics-assisted coherent MIMO radar systems
Special Issue Information
Dear Colleagues,
The exponential advancement of artificial intelligence (AI) and machine learning (ML) has a significant impact on communication systems and networks, offering opportunities for innovation, efficiency, and enhanced security. We aim to investigate the role of AI and ML in enhancing security in optical communication networks, focusing on physical layer security, authentication, identification, monitoring, and emerging attacks. This issue will focus on advancing research, groundbreaking innovations, and practical applications for physical layer security (PLS), addressing the critical aspects of physical layer trustworthiness, integrity, and security. It will span information theory to practical implementation, emphasizing authentication, identification, monitoring, and attack detection through AI and ML techniques. We encourage authors to submit high-quality, original contributions on the creation of robust and efficient security mechanisms that can shield optical networks from evolving threats, enabling the design and implementation of secure optical communication systems. In addition, research on ensuring the privacy of data transmission across diverse domains, including optical telecommunications and critical infrastructure networks, by implementing AI and ML techniques will be considered. The broad range of topics related to this Special Issue’s focus on physical layer security include but are not limited to the following: security requirements from the perspective of operators and service providers; security plane architecture and communication security from a vendor perspective; information theory and information security; security aspects in fiberoptic communication; ML in PHY(QKD); digital twin, security and AI solutions for PLS; practical approaches to PLS; and the assessment of trustworthiness and required metrics using ML techniques.
Dr. Pantea Nadimi Goki
Dr. Giovanni Serafino
Guest Editors
Manuscript Submission Information
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Keywords
- physical layer security
- attacks
- identification
- authentication
- optical communication networks
- machine learning
- artificial intelligence
- trustworthiness
- monitoring
- privacy
- integrity
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