Every new generation of mobile networks brings significant advances in two segments, enhancement of the network parameters within the legacy technologies and introduction of new technologies enabling new paradigms in designing the networks. In the first class of enhancements the effort is to increase data rates, improve energy efficiency, enhance connectivity, reduce data transmission latency etc. In the second class of innovations for 6G and 7G, we anticipate focus on optimum integration of advanced ML and AI in general, and quantum computing with the continuous interest in the satellite networks for optimal quantum key distribution . By introducing quantum technology 7G will be able to speed up computing processes in the net, enhance network security as well as to enable distributed QC, which is a new paradigm in computer sciences. Using advanced networks as a basic ingredient of inter system integration, here we focus only on the second segment of anticipated innovations in networking and present a survey of the subset of potential technology enablers for the above concept with special emphasis on the inter dependency of the solutions chosen in different segments of the network. In Section II, we present several anticipated 6G/7G (system of systems type) network optimization examples resulting in a new paradigm of network optimization indicating a need for quantum computing and quantum computing based optimization algorithms. In Section III we survey work on quantum cryptography and QKD.
Every new generation of mobile networks brings significant advances in two segments, enhancement of the network parameters within the legacy technologies and introduction of new technologies enabling new paradigms in designing the networks. In the first class of enhancements the effort is to increase data rates, improve energy efficiency, enhance connectivity, reduce data transmission latency etc. In the second class of innovations for 6G and 7G, we anticipate focus on optimum integration of advanced ML and AI in general, and quantum computing with the continuous interest in the satellite networks for optimal quantum key distribution . By introducing quantum technology 7G will be able to speed up computing processes in the net, enhance network security as well as to enable distributed QC, which is a new paradigm in computer sciences. Using advanced networks as a basic ingredient of inter system integration, here we focus only on the second segment of anticipated innovations in networking and present a survey of the subset of potential technology enablers for the above concept with special emphasis on the inter dependency of the solutions chosen in different segments of the network. In Section II, we present several anticipated 6G/7G (system of systems type) network optimization examples resulting in a new paradigm of network optimization indicating a need for quantum computing and quantum computing based optimization algorithms. In Section III we survey work on quantum cryptography and QKD.
A comprehensive study has been recently made of post-quantum ( q -) and q -cryptography algorithms and their applicability in advanced networks. An insight is provided into the candidate algorithms to replace RSA and ECC schemes. The results of the research suggest that most probably post-q schemes will dominate 6G networks and due to implementation complexity q-solutions will be fully employed in 7G. Since most of these works focus on the cryptography algorithms in this paper, we cover the most important segments of advanced communications and q- networks design that will have to support these algorithms in the future as well as distributed quantum computing applications in general. For the applications in 6G/7G ACCESS networks, existing work on q-key distribution over sub-optical bands, surveyed in Section II, is essential. As a next step, for 6G/7G CORE n et designers, results on dynamic q- networks topology design are reviewed in Section III and its optimization in Section IV including the work on q- networks stability surveyed in Section V. Due to the limited space, survey of the work on q- networks designed over satellite constellations, which are bases for global systems, is left for a separate paper. In Section VI we present new optimization frameworks for cost efficient q-network topology design and optimum resource (capacity and secrete key rates) allocations in these networks.
Recently significant effort has been invested in studying commonalities of human brain operation and advanced algorithms for machine learning to answer the question: Can the learning mechanisms, identified in the operation of the brain, be mimicked in artificial neural networks to enhance the learning efficiency with simultaneous reduction in complexity and power consumption. At the same time, machine learning algorithms, on their own, become increasingly complex, resulting in complex neural networks. To speed up the machine learning algorithms, research on 7G networks will be looking for new computing technologies, like quantum (q-) computing (QC), and new models for complex networks that will enable us to efficiently control/optimize the processes run on them. In this paper, under the umbrella of well-established complex networks theory, we provide a unified presentation of how quantum computing, implemented on near-future computers, can enable solving various problems in the above disciplines, otherwise difficult to solve by using classical (c-) approaches. The emphasis is on the commonalities in QC applications and modeling for the different systems listed above. For 7G network designers, the survey is expected to provide an insight into how much the research results in natural, QC based sciences can be integrated into new network paradigms to support above initiatives.
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.
In general, quantum technologies and quantum algorithms possess transformative potential for next-generation communication systems. Particularly with the unprecedented data speeds, ultra-low latency, and seamless global connectivity promised by 6G, these technologies are expected to offer significant opportunities for telecommunications and mobile network operators. The integration of quantum computing can play a role in optimizing network operations, improving resource management, reducing energy consumption, and increasing data processing efficiency. For mobile network operators, this will result in significant progress in key performance indicators (KPIs) such as scalability, reliability, and security. Furthermore, quantum cryptography will be of critical importance by introducing new security standards for real-time data protection. This paper will focus on a mobile network operator�s perspective and explore potential solutions. It will assess the synergy between quantum technologies and telecommunications, focusing on key topics such as network latency, bandwidth optimization, and energy efficiency. By leveraging quantum computing, the paper will explore how future telecommunications networks can become faster, more secure, and more sustainable.
Abstract Sixth Generation (6G) communication networks are anticipated to advance the fifth generation technologies as well as introduce new revolutionary technologies to deliver aggressive data rates, end-to-end latency, reliability, energy efficiency, security, network capacity, and mobility requirements of the future innovative applications. To deliver these demands, ultra-fast and secure computing capability for processing a huge amount of data, application-related tasks, and resource management algorithms will be required. Many 6G applications will use advanced learning techniques that work on large data sets and their working can be made more efficient with the help of Quantum Computing (QC) instead of conventional classical computing. In this paper, we provide an overview of QC and 6G networks and highlight the benefit of integrating these two technologies. We briefly review the recent work and present a framework for QC-assisted 6G networks. We also discuss four use cases of QC in 6G networks, including quick task offloading, fast optimization algorithm results, efficient machine learning techniques, and improved security. Finally, we discuss several open challenges of using QC in the context of 6G network applications.
The introduction of 6G networks presents unprecedented challenges in data transmission speed and efficiency, motivating the investigation of AI-Enabled Quantum Networks. This paper investigates the integration of artificial intelligence (AI) algorithms into quantum networks to optimize data transmission for 6G. Quantum networks can adapt dynamically to varying network demands and traffic patterns through using AI for resource allocation, qubit management, and gate optimization. The study investigates potential applications of AI-enabled quantum networks in scientific research, financial services, healthcare, and telecommunications, highlighting the benefits of faster collaboration, enhanced data security, and improved connectivity. However, challenges such as developing robust AI algorithms for quantum systems and ensuring network security must be addressed. The integration of AI and quantum technology opens new opportunities for advanced communication networks in 6G, promising innovations in real-time data processing, predictive modeling, and personalized services. As technological challenges are overcome and quantum network capabilities are developed, the potential for penetration of applications and services appear limitless.