Quantum Mechanics is a branch of science that describes the interactions between photons and electrons. Quantum science completed more than 100 years of existence with pioneers research made by Max Planck to explain black body radiation. This theory, historically speaking, is new by comparison with classical physics. However, quantum physics is revolutionary. It adds novel scientific concepts about our universe and the atomic world, breaking some existing concepts of Isaacs Newton’s Laws in classic physics and Pierre Laplace’s calculus. Contribution for the quantum mechanics provided by notorious scientists such as Niels Bohr and Albert Einstein paved the way for quantum computation and quantum communications. Nowadays, quantum mechanics are being engineered to quantum technologies to start a new scientific revolution and perhaps move our society for Industry 5.0 and Society 5.0. It is known that by 2030 the Big Data will be even more prominent with the number of devices connected to the Internet. Therefore, it is vital to engineering a 6G Radio that is cognitive, fast to predict events, and prevent incidents. For this, 6G Radio must have Artificial Intelligence operating with machine learning with the combined quantum computer superpower to process and harness the incommensurable amount of big data in favor of excellent service level agreements (SLAs) and Quality of Experience (QoE). Thus, this is the proposal of this study presented here.
Quantum Mechanics is a branch of science that describes the interactions between photons and electrons. Quantum science completed more than 100 years of existence with pioneers research made by Max Planck to explain black body radiation. This theory, historically speaking, is new by comparison with classical physics. However, quantum physics is revolutionary. It adds novel scientific concepts about our universe and the atomic world, breaking some existing concepts of Isaacs Newton’s Laws in classic physics and Pierre Laplace’s calculus. Contribution for the quantum mechanics provided by notorious scientists such as Niels Bohr and Albert Einstein paved the way for quantum computation and quantum communications. Nowadays, quantum mechanics are being engineered to quantum technologies to start a new scientific revolution and perhaps move our society for Industry 5.0 and Society 5.0. It is known that by 2030 the Big Data will be even more prominent with the number of devices connected to the Internet. Therefore, it is vital to engineering a 6G Radio that is cognitive, fast to predict events, and prevent incidents. For this, 6G Radio must have Artificial Intelligence operating with machine learning with the combined quantum computer superpower to process and harness the incommensurable amount of big data in favor of excellent service level agreements (SLAs) and Quality of Experience (QoE). Thus, this is the proposal of this study presented here.
Quantum mechanics is a part of physics that studies the interactions of matter, light, and particles at the atomic and subatomic levels. Since its initial concepts in the early 1900s built upon extensive research of Nobel laureates such as Max Planck, Niels Bohr, Albert Einstein, and Richard Feynman, amongst others to the first proposed quantum computers by Paul Benioff in 1980, the concept of quantum technologies has evolved. Two central studies derived from quantum mechanics that can support and revolutionize future wireless technologies are quantum computers and quantum communications. The investigation for building the next generation of wireless networks has begun. Therefore, many technological opportunities for applying innovative solutions and advanced concepts are on the table as an option to unlock the full potential of 6G for providing an intelligent, superfast, and secure network. Having said that, quantum mechanics come into play to offer a breakthrough opportunity that will change the world since the popularization of the Internet, and it will propel 6G use cases to be remarkably successful, but only if quantum physics can be engineered and converged into the forementioned quantum technologies to support the achievement of Society 5.0. Therefore, overcoming the quantum challenges, 6G can benefit in many ways. One of them is Quantum computing (QC) that will surpass the computational capabilities of classic computers limited by binary transactions known as bits to resolve future challenges using quantum states to process information in quantum bits (Qubits). Correspondingly, quantum computing will merge with Artificial Intelligence (AI) to create a new model known as Quantum Machine Learning (QML) to deal with the exponential growth of Big Data faster than any existing computational model. In Addition, quantum communications will deliver a safer network, utilizing Quantum Key Distribution (QKD) and inaugurate the next generation of the Internet, much safer for all. Thus, this paper presents a holistic overview of Quantum as a service (QaaS) as a future deployment in the 6G architecture, but only if quantum technologies can be mastered in the next upcoming years. Most likely that QaaS will become available for commercial purposes by the hyperscalers, the ones able to cope with the total cost of ownership (TCO) of these state of art technologies. This paper is divided by an introduction that summarizes the foundation of quantum mechanics, its laws, and the researchers’ pioneers responsible for setting the principles used to create the next generation of quantum technologies. In Section 2, there is a presentation of the core parts of quantum physics used to create quantum computers and quantum communications services, which includes the technological challenges to mature these technologies. Finally, in Section 3, the conclusions are presented.
While the commercial deployment of 5G networks and beyond is a reality, the first work for the definition and study of 6G networks has started. The scientific community agrees that these networks will be characterised by a very high spatial density of access points, heterogeneity of access technologies, an increased number of users per access point, and demand for ubiquitous connectivity that must combine ultra-low latency, very high bandwidth, and high energy efficiency [1, 2]. Among the emerging challenges, holographic communications, high-precision manufacturing, the ubiquitous introduction of intelligence, and the incorporation of new technologies based on sub-terahertz (THz) or Visible Light Communications (VLC) are real issues. These are taking place in a truly three-dimensional coverage framework, integrating terrestrial and aerial radio to meet the needs with cloud-based capabilities where and when needed (on-demand). Radio frequencies are used in wireless telecommunications, but the need for very high throughput requires wider bandwidths, hence very high frequencies, in particular THz bands. Moving to a higher frequency range—from 100 GHz to 10 THz—is expected to significantly increase the bandwidth of the radio channel, which will make it possible to serve a significant number of users. In this case, we are not talking about the connection of cell phones, tablets, or computers (and even smart cars)—we are considering the use of Internet of Things (IoT) devices, which within one base station can be quite a lot. Therefore, the technologies for beamforming, device location, etc., developed for the 5G generation that is just being implemented now should also remain but will be used at higher frequencies [3]. For which 6G is primarily intended, IoT solutions have been given a particular name: ‘human-machine-things’. They involve three elements in the system: a person as a physical carrier; an intelligent device with which the person interacts; collects data and executes commands from an application running on the person's device [4]. The 6G radio networks will provide the means of communication and data gathering necessary to accumulate information. Still, a system's approach will be required for the 6G technology market as a whole involving data analytics, artificial intelligence (AI), and next-generation computation capabilities via HPC and quantum computing [3, 5]. This tremendous amount of data may be harnessed, with strong processing and learning capabilities, to manage the network at different levels. To this end, quantum computing methods can play a significant enabling role and can provide a guaranteed security platform. Towards provisioning this massive connectivity and efficiently processing the voluminous data available at the user and network sides, quantum-powered computing methods have a strong potential in realising the ambitions of a service-driven, fully intelligent 6G communication network. There is every reason to believe that the integration of quantum technology can improve the throughput, efficiency, and security of 6G networks. In addition to the advantages mentioned above, this technology also has benefits in computing speed, guaranteed security, and minimal storage requirements. This makes it ideally suited for various future quantum communication network applications. Research is needed on many fronts to evaluate the potential opportunities of quantum computing in 6G applications. In 5G, a functional division is operated in both the RAN and core networks to meet the ultra-low latency and ultra-high efficiency requirements of 5G verticals. Notably, RAN functions are split into cloud-deployed services with interfacing capabilities. This new architecture has a significant impact on the efficient implementation of security processes [6]. One of the key challenges in deploying secure 5G networks is analysing how current cryptographic algorithms for secure authentication and data transmission can adapt to provide secure authentication between services and secure data encryption while ensuring that stringent efficiency requirements are met [7]. The powerful parallel processing capability of quantum search algorithms can be leveraged to solve large-scale wireless optimisation problems. (1) Is this ‘beyond 5G?’ This topic is highly exploratory and undoubtedly beyond the boundaries of core 5G R&D. (2) What are the new features and key challenges? Classically, the mutual information between the channel input and output must be maximised. For quantum channels, the capacity must be redefined. Quantum channels can increase the achievable capacity. As a result, error correction without redundancy is possible on noisy channels. Quantum computers can enable exponentially complex combinatorial ML decoding in classical systems [5, 6]. To cope with latency-critical scenarios such as automated cars and medical applications, communication must be accomplished in a concise time. Achieving latency of only a few milliseconds is a real challenge. To achieve low latency and ultra-high reliability, it is essential to develop powerful high-end processors that consume little power. Quantum computing seems to be a reliable solution to this issue [8]. With variable quality of service (QoS) requirements, a variable radio resource must be allocated to the user. This can be of variable bandwidth, variable power, or both. Another challenging aspect of 6G is that with the propagation frequency, the signal can attenuate quickly and have a high penetration loss at high frequencies [9]. The signal is also automatically attenuated when accessing homes, residences, or workplaces. As the frequency increases, radio waves attenuate and may have difficulty penetrating the walls of buildings and homes while affecting users' QoS requirements. Therefore, it is very important to develop stable, fast and accurate quantum algorithms to handle 6G communication requirements by dynamically allocating variable resources [10]. The current 5G standard does not address the issue of quantum computing but relies on traditional cryptography. The development towards cloud and edge native infrastructures is expected to continue in 6G networks. While large-scale quantum computing can be expected to take a longer duration, it is time to prepare for the shift to cryptography that is secure in the post-quantum world. According to current knowledge, contemporary symmetric cryptography remains secure for the most part, even after the advent of quantum computing. Furthermore, authentication by a physical layer signature, such as RF fingerprinting, and some other technologies, such as randomisation of MIMO transmission coefficients, coding, etc., could potentially be used in 6G [5, 11]. Whether it is for the optimisation of heterogeneous resources in 6G networks that result in the solution of ‘NP-complete’ combinatorial problems, for the compensation of non-linear effects of a communication chain or the optimisation of MIMO transmitter pre-coding matrix, future network nodes and devices will have to be equipped with learning and decision-making capabilities through AI and machine learning, so that they autonomously optimise their operation in response to changes in the environment [5]. In this context, the use of optimisation techniques based on quantum computing and AI applied to the field of 6G networks could be of considerable interest. Besides, quantum computing allows NP-hard optimisation problems to be solved in linear time, making it possible to solve and execute network optimisation problems in a much faster time, even in real-time [5, 11]. Regulatory and standardisation work will impact our future technology solutions in 5G networks and beyond. Protecting individual privacy and identity has long been a challenge for standards bodies, as countries have very different perspectives and regulations in this area. International standards bodies such as JTC 1 have committees working on privacy frameworks and are making progress, but there is still much to be done [13]. To conclude, we believe that our readers will find this opinion piece useful in giving an overview of the importance of Quantum Computing/communications in shaping the next communication systems and its security platforms. This is a technology in its infancy and a lot of research remains to be carried out to achieve sustainable solutions and overcome the current challenges. The use of intelligent systems (AI, ML and other techniques) will be essential in achieving solutions faster and providing sustainable outcomes. But IoT devices as well as cloud and edges nodes must be AI-ready and be able to support the use of intelligent algorithms.
2025 is the year UNESCO selected to celebrate 100 years of this novel science, quantum mechanics, based on Heisenberg’s “uncertainty principle” discovery. However, quantum mechanics began with the discovery of quantum packets of energy emission formulated by the German physicist Max Planck, and it incorporated additional discoveries and principles from Albert Einstein, Niels Bohr, Heisenberg, Pauli, de Broglie, and many others in the early 1900s. Since then, many advancements and breakthroughs have been made. Such scientific contributions have influenced the culture and technology of humanity from the 20th century onwards, with the first quantum revolutions bringing innovations in technology and engineering, including the omnipresent light amplification by stimulated emission of radiation (Laser), magnetic resonance imaging (MRI), microprocessor manufacturing and design for computers and nuclear energy. Thus, at the beginning of the Second Quantum Revolution in the 21st century, amid a new wave of novel quantum technologies promising to create the 5th Industrial Revolution and transform humanity, a brief history of these marvellous sciences is condensed, connecting the wonders of the new quantum technogenesis that is being forged, linking its past with classical mechanics and also with novel relativistic mechanics. Understanding these developments highlights the significance of quantum technologies shaping our future and what lies ahead for us. This article explores technologies that are presently under research and development (R&D) in the quantum physics realm, including quantum computing, quantum cryptography, quantum sensing and metrology, and quantum simulation. It also discusses emerging careers in the quantum field and the unresolved mysteries that continue to challenge scientists. The discussion follows the ancient griot tradition of storytelling, a method that the distinguished physicist, great professor, and Nobel laureate Richard Feynman encouraged us to use to explain complex scientific ideas.
Secure your expertise in the next frontier of wireless technology with this essential book, which provides a deep dive into the integration of machine learning and quantum computing to build the necessary infrastructure for 6G communication networks. Despite the potential benefits of 6G, the technology to enable its realization is not yet available. As a result, the development of technology to solve these challenges must be met before we can start working towards 6G. The primary applications of machine learning within 6G are to create necessary infrastructure advantages as the technology matures. Additionally, 6G communication networks use quantum computing to detect, mitigate, and prevent security vulnerabilities. By integrating machine learning and quantum computing into 5G and 6G technology, intelligent base stations will be able to make decisions for themselves, and mobile devices will be able to create dynamically adaptable clusters based on learned data. This book highlights the role of real-time network learning and the integration of quantum computing, machine learning, and quantum machine learning to enhance service quality. It provides a deep dive into the interplay of these technologies within 6G networks, starting from 5G fundamentals. The book elaborates on how these advanced technologies will underpin 6G’s architecture to meet comprehensive service demands, including those for smart city applications requiring extensive coverage, ultra-low latency, and reliable connectivity. The book details how the synergy between quantum computing, machine learning, and 6G technologies will transform communications, revolutionize markets, and enable groundbreaking applications globally. Readers will find the volume: Explores real-world scenarios for illustrating the integration of quantum computing and machine learning in 6G;Covers an extensive range of applications to illustrate the full picture of 6G that implements machine learning and quantum computing approaches;Offers expert insights through a comprehensive collection of literature reviews and research articles;Introduces the interdisciplinary innovations and potential of 6G across multiple industries. Audience Scientists, industry professionals, researchers, academicians, instructors, and students working in quantum computing and machine learning, especially in the context of advanced wireless communication technology.
Future 6G networks are expected to surpass the advances made in 5G, by providing the faster speeds, lower latency and extended coverage needed for emerging transformative applications, while at the same time achieving greater energy and spectral efficiency, as well as enhanced security and reliability. While 6G is currently in its initial phases of development and standardization, it is already foreseen to incorporate not just incremental technical enhacements but also pioneering innovations compared to its forerunner, 5G. Indeed, quantum technologies are expected to play an important role in 6G. This goes beyond mechanisms such as quantum key distribution for secure communications; it includes the integration of quantum computing for advanced data processing within 6G networks. As 6G networks are set to integrate artificial intelligence and machine learning even more intrinsically into their operation, the concept of quantum machine learning (QML) emerges as a promising opportunity to enable swift data processing, network optimization, and increased security and privacy. In this presentation, we will look at the fundamentals of quantum computing and quantum machine learning, explore the possibilities they offer for future 6G networks, and the potential for revolutionary advances they offer, while presenting some the important challenges associated with their integration into 6G networks.
In the field of Internet service evolution, classical and quantum paradigms are often seen as distinct and separate research areas. Typically, the classical Internet is perceived as a foundational communications infrastructure for the emerging quantum Internet, mainly providing essential services such as synchronization, signaling, control, and feedback. Current quantum Internet research requires a radical transformation of physical layer devices, often leading to the obsolescence of existing classical infrastructures. To address this challenge, in this work we introduce a new hybrid approach for the future development of the quantum Internet. Specifically, we will delve into various mechanisms and technologies that facilitate the integration of quantum networks with future 6G networks. Our goal is to develop a complete model for a hybrid quantum-classical Internet designed for future generation 6G in order to jointly and efficiently support both quantum and classical communications. In particular, we explore an innovative hybrid datalink layer architecture that is critical for effectively managing the diverse nature of quantum and classical data traffic and security. The main advantage of our model lies in the integration of new quantum hardware at the physical layer while leveraging existing advanced classical infrastructure. Our model is proposed as a step forward in the harmonization of quantum and classical Internet technologies, paving the way for a secure and fast future 6G architecture.