The potential application of quantum computing in the communication networks

Riccardo Bassoli, Holger Boche, Christian Deppe +4 more

Dong Chen, Jiemin Zhang

With the continuous progress of quantum computing and quantum communication technology, the application of quantum algorithms in future communication networks is increasingly promising. Quantum algorithms have computing power beyond traditional algorithms and can effectively improve the performance and security of communication networks, especially in the field of electronics and communication engineering, showing great potential. In this paper, the application of quantum algorithms in future communication networks is discussed in depth, focusing on the analysis of quantum communication protocols, the application of quantum computing in network optimization, and the innovative methods of quantum algorithms in enhancing network security. By systematically analyzing the basic principles, application examples and development trends of quantum algorithms, this paper aims to provide theoretical support and technical reference for the design and realization of future communication networks. Finally, this paper summarizes the current challenges in the application of quantum algorithms and looks forward to the future development direction of its wide application in electronics and communication engineering.

Riccardo Bassoli, Holger Boche, Christian Deppe +4 more

Huang Yuhong, Chunfeng Cui, Pan Cheng-kang +5 more

Quantum computing is a promising technology that has the potential to revolutionize many areas of science and technology, including communication. In this review, we discuss the current state of quantum computing in communication and its potential applications in various areas such as network optimization, signal processing, and machine learning for communication. First, the basic principle of quantum computing, quantum physics systems, and quantum algorithms are analyzed. Then, based on the classification of quantum algorithms, several important basic quantum algorithms, quantum optimization algorithms, and quantum machine learning algorithms are discussed in detail. Finally, the basic ideas and feasibility of introducing quantum algorithms into communications are emphatically analyzed, which provides a reference to address computational bottlenecks in communication networks.

Engin Zeydan, Chamitha de Alwis, Rabia Khan +4 more

As the world prepares for the advent of 6G networks, quantum technologies are becoming critical enablers of the next generation of communication systems. This survey paper investigates the convergence of quantum technologies and 6G networks, focusing on their applications, opportunities and challenges. We begin with an examination of the motivations for integrating quantum technologies into 6G, investigating the potential to overcome the limits of classical computing and cryptography. We then highlight key research gaps, particularly in quantum communication, quantum computing integration and security enhancement. A comprehensive overview of quantum technologies relevant to 6G, including quantum communication devices, quantum computing paradigms, and hybrid quantum-classical approaches is provided. A particular focus is on the role of quantum technologies in enhancing 6G Radio Access Networks (RAN), 6G core and edge network optimization, and 6G security. The survey paper also explores the application of quantum cryptography with a focus on Quantum Key Distribution (QKD), Quantum Secure Direct Communication (QSDC) and quantum-resistant cryptographic algorithms and assesses their implementation challenges and potential impact on 6G networks. We also discuss the significant challenges associated with integrating quantum technologies into existing communications infrastructures, including issues of technological maturity, standardization, and economic considerations. Finally, we summarize the lessons learned from current research and outline future research directions to guide the ongoing development of quantum-enabled 6G networks.

Cheng Li Wu