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Comparative Study of Quantum and Classical Error Correction for Future Quantum-6G Networks

Siddharth Kumar Das, Riccardo Bassoli, Roberto Ferrara, Janis Nötzel, Christian Deppe, Frank H. P. Fitzek, Holger Boche

Published Mar 17, 2023• 0 citations
Publisher

Abstract

The paper compares quantum and classical error correction scheme with the aim for a pathway to 5G beyond networks where there will be a notion of quantum computation in the current classical communication architecture.
DOI
10.36227/techrxiv.22294096

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Comparative Study of Quantum and Classical Error Correction for Future Quantum-6G Networks

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The paper compares quantum and classical error correction scheme with the aim for a pathway to 5G beyond networks where there will be a notion of quantum computation in the current classical communication architecture.

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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. 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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. 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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.
Bridging the gap between classical and quantum communication is a well sought-after topic with significant potential in fortifying the networks of the future. In that direction, we have attempted to analyse realistic quantum channels through the lens of classical communication frameworks. To achieve this, we have developed a simulation environment that integrates classical link-level simulator with a quantum simulator, allowing an in-depth assessment of quantum noise impacts on 5G-compliant error correction code (ECC). We focused on the performance of low density parity check (LDPC) codes and polar codes under the influence of these quantum models. The comparative analysis, primarily on bit error rate (BER) performance demonstrates a clear advantage for LDPC codes across both quantum channel under identical simulation conditions. The results of this study offer valuable insights into how classical ECC perspectives can be applied to quantum channels, guiding the selection of appropriate error correction schemes tailored to specific quantum channel models.
In upcoming generations of wireless communication (6G), Quantum Information Technology (QIT) will be integrated for high computational speeds and unprecedented security features. Quantum states are very delicate and may be lost or suffer from excessive noise as a result of decoherence during transmission. This especially applies to long-distance quantum links that are required for a global 6G network. The use of Quantum Error Correction (QEC) techniques will be necessary in order to achieve fault-tolerant quantum communication. In this work, the most actionablle QEC and hybrid (quantum-classical) error correction techniques are analyzed, especially with respect to the difficult channel conditions and high Key Performance Indicators (KPI) regarding 6G. In particular, the error suppression, qubit overhead, and decoding time required for various codes (Surface Code, Steane Code, hybrid Reed-Solomon (RS)/Turbo Codes, etc.) will be analyzed in the context of a 6G quantum channel (free-space or noisy fiber) to provide 6G. In the wireless 6G network, the simulation will show that while high-distance QEC codes provide the best ultimate logical error suppression, the enormous resource costs and 6G’s strict latency requirements will lead to the first proposed hybrid classical-QEC.
With the increasing number of commercial 5G deployments, research on beyond 5G (B5G) and 6G has started in earnest. Although it is too early to clearly identify what 6G systems will look like or how they will be designed, it is certain that 6G systems will support novel use cases with challenging key performance indicators (KPIs), which will be empowered by new enabling technologies and network architectures. In parallel with the evolution of cellular systems from 5G toward 6G, quantum information technology (QIT) has been evolving rapidly in recent years in terms of quantum communications and quantum computing. It is envisioned that QIT will enable and boost future 6G systems from both communication and computing perspectives. For example, secure quantum communications such as quantum key distribution can be leveraged to improve 6G security. This article aims to provide a technology-driven and visionary description and exploration on how QIT can be leveraged for future 6G wireless networks.