Special issue on quantum technologies for communication systems

Quantum technologies hold the potential to revolutionize classical technologies and their emerging applications in communication networks and mobility. This potential is expected to grow alongside the advancement of quantum computation-capable devices. Currently, quantum devices are at the noisy intermediate-scale quantum (NISQ) level and can support only a few hundred physical qubits. While these devices remain constrained in scale, early fault-tolerant quantum hardware is capable of demonstrating the quantum advantage, the ability to outperform classical counterparts in specific computational tasks. This capability is essential for enhancing coordination of 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 constraints of current large-scale 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 approximately by 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 to seek original contributions to various aspects of QML-based system architectures, protocols, resource management, error correction, and other technologies in communication systems. Furthermore, 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. Despite significant interest in this field from both academia and industry, many important questions remain. This special issue of JCN presents five high-quality papers which are categorized under (i) theory, (ii) communications and networks, and (iii) applications. In the following, we will introduce the topic section categories and corresponding papers included in this Special Issue.