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“QUANTUM TECHNOLOGIES FOR COMMUNICATION SYSTEMS” PUBLICATION DATE: August / September 2025
Quantum technologies hold the potential to revolutionize classical technologies and their emerging applications to
communication networks and mobility. This potential is expected to grow alongside the development of more
advanced quantum computation-capable devices. Currently, quantum devices are at the noise intermediate-scale
quantum (NISQ) level, supporting up to a few hundred physical qubits. Despite the current limitations, early faulttolerant quantum hardware in the NISQ phase has already demonstrated the quantum advantages
This capability is essential for coordinating autonomous and distributed systems such as low Earth orbit (LEO)
satellites, autonomous driving vehicles, and complex infrastructure required by the hyper-connected 6G
communication networks. Especially in artificial intelligence (AI) research domains, parameterized quantum circuits
used in quantum algorithms, quantum optimization, and quantum machine learning (QML) can implement various
functionalities of classical neural network architectures with significantly fewer parameters and computation
resources. This can substantially reduce the latency and memory requirements of current large-sized classical neural
network frameworks, including diffusion-based generative computer vision algorithms and large language models.
According to the current roadmaps for quantum computer development, the number of qubits is expected to greatly
increase, and the beyond-NISQ era is set to emerge by around 2026. This highlights the need for early contributions
to explore the potential impact of quantum algorithms and QML on emerging communication system design and
future applications. Towards unleashing the full potential of quantum algorithms and QML, this special issue focuses
on quantum algorithms and QML principles, algorithms, and use cases and seeks original contributions to various
aspects of QML-based system architectures, protocols, resource management, error correction, and other technologies
in communication systems. On the other hand, there is also an increasing interest in applying classical AI techniques
for solving problems within quantum computing and computation, such as in quantum software engineering,
quantum circuit design, and optimizing quantum optimization algorithms. Consequently, we also seek contributions
that apply classical communication techniques in various aspects of quantum computing.
Topics of interest include, but are not limited to:
Guidelines according to the IEEE/KICS JCN Guidelines: https://www.jcn.or.kr/html/?pmode=InformationforAuthors
Guest Editors:
Prof. Soo Yong Shin, Kumoh National Institute of Technology, Korea / wdragon@kumoh.ac.kr
Prof. Zhu Han, University of Houston, TX, USA / zhan2@uh.edu
Dr. Shaukat Ali, Simula Research Laboratory, Norway / shaukat@simula.no
Dr. Samuel Yen-Chi Chen, Wells Fargo Bank, New York, USA / yen-chi.chen@wellsfargo.com
Prof. Yuanwei Liu, The University of Hong Kong, China / yuanwei@hku.hk
Prof. Soohyun Park, Sookmyung Women's University, Korea / soohyun.park@sookmyung.ac.kr
Prof. Joongheon Kim, Korea University, Korea / joongheon@korea.ac.kr
JCN is a high-quality bimonthly archival journal, published by the Korean Institute of Communications and Information Sciences with the technical co-sponsorship of the IEEE Communications Society, covering the fields of Communication Theory and Systems, Wireless Communications, and Networks and Services. JCN began publication in March 1999.