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International Conference on Electronic Information Engineering and Computer Communication (EIECC)

Comparison of modulate and demodulate methodologies for quantum communication

Hui Zhang

Published May 4, 2022• 0 citations
Publisher

Abstract

Quantum communication is a theory based on the idea that quantum states can be transferred from one place to another. This theory has several advanced features. Specifically, it has high security, low time cost and low power overhead. Quantum information can make the execution of tasks much less efficient. However, much research has been done to achieve quality control by proposing utterly new security algorithms. The modulation and demodulation tasks of QC have not been sufficiently studied. Therefore, the modulation and demodulation methods are systematically summarised and analysed according to the two types of "signal type" and "modulation method type", respectively. In summary, PSK modulation outperforms OOK modulation in SRM-based multi-user detection schemes. The serious shortcomings of generalised secrecy modulation in terms of information-theoretic security mean that the security of GCM is not good. Moreover, there are many practical problems still required to be addressed. For example, the computational complexity characterisation and optimisation with correlation type receivers. Especially for ultra-high SE improvement have a large N parameter. Switching the slits at a reliable and efficient pace is a challenge. The high SE reduce the importance of speed. The complexity of the ML decoder combing with the joint modulation/coding should be explicitly modelled. Finally, the design of optical set-up in combination with amplifier structures recovering the loss due to MPD design.

DOI
10.1117/12.2634826

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Quantum communication is a theory based on the idea that quantum states can be transferred from one place to another. This theory has several advanced features. Specifically, it has high security, low time cost and low power overhead. Quantum information can make the execution of tasks much less efficient. However, much research has been done to achieve quality control by proposing utterly new security algorithms. The modulation and demodulation tasks of QC have not been sufficiently studied. Therefore, the modulation and demodulation methods are systematically summarised and analysed according to the two types of "signal type" and "modulation method type", respectively. In summary, PSK modulation outperforms OOK modulation in SRM-based multi-user detection schemes. The serious shortcomings of generalised secrecy modulation in terms of information-theoretic security mean that the security of GCM is not good. Moreover, there are many practical problems still required to be addressed. For example, the computational complexity characterisation and optimisation with correlation type receivers. Especially for ultra-high SE improvement have a large N parameter. Switching the slits at a reliable and efficient pace is a challenge. The high SE reduce the importance of speed. The complexity of the ML decoder combing with the joint modulation/coding should be explicitly modelled. Finally, the design of optical set-up in combination with amplifier structures recovering the loss due to MPD design.
The key features of 5G, such as ultra-reliable low latency (URLLC) and massive machine-type communication (mMTC), are designed to address the need for low latency and the ability to connect a large number of devices in the IoT context. To support these constraints, mobile devices transmit information without previously establishing a connection with the base station (BS). This requires the Base Station to detect in real-time the active users (process known as Active User Detection (AUD)). With classical processors, one can employ the Maximum Likelihood (ML) method (the optimal detector, but suffers from high complexity and delay), or suboptimal ones (which are simpler, but less reliable). Meanwhile, quantum algorithms, particularly Durr and Hoyer (DHA) algorithm, addressing minimum searching problems, can significantly reduce complexity while keeping good performances. However, these algorithms were designed for generic problems, and their initialization and parameterization are blindly done. Nonetheless, we can have access to prior information on the system’s behavior. Therefore, in this paper, we aim to adapt and improve these quantum algorithms by using prior knowledge on the system for the AUD problem. We first propose a novel algorithm, the Improved Iterative Minimum Searching Algorithm (IIMSA) where we define more efficiently the parameters. Then, further enhancements of IIMSA are obtained thanks to a better initialization of the algorithms by exploiting classical preprocessing of the received signals with classical Conventional Correlation Receiver (CCR) or Zero Forcing (ZF). The obtained results show that these proposed algorithms operate more efficiently (i.e., less complexity with better accuracy).
In recent years, as computational power increases, the traditional encryption methods are becoming increasingly vulnerable to attacks and thus have some safety issues. Therefore, the application of quantum communication has become increasingly widespread, and more technologies related to quantum communication have been invented. This article provides an overview of the differences between quantum communication and traditional encryption in terms of their advantages, disadvantages, security, and the challenges they face in applications. Indeed, the unique characteristics of quantum communication, like quantum superposition and quantum entanglement, provide quantum communication with good security. Furthermore, quantum communication has several advantages, like quantum key distribution, which ensures secure communication, high capacity, high speed, resistance to eavesdropping, and error correction. However, the traditional encryption is still widely used. The traditional encryption, which relies on mathematical algorithms and offers mature encryption methods like Advanced Encryption Standard and Rivest-Shamir-Adleman, must have advantages over quantum communication. Therefore, a comprehensive comparison between traditional encryption and quantum communication is essential to understand their respective roles in the future of secure information exchange.
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.
Quantum-Noise Randomized Cipher (QNRC) is a potentially information-theoretic secure physical-layer encryption method for high-speed and long-distance fiber communications. In order to solve the problem that the modulation and demodulation of M-ary Y-00 ciphertext signal in QNRC system are limited by the ADC chip with high sampling rate and high conversion depth, a novel realization of PSK-QNRC system based on series structure of multiple phase modulators (PM) is proposed, and the performances of the proposed scheme is verified by using commercial simulation software in this paper. The simulation results show that, the 126-PSK QNRC system at 10 Gbit/s over 1000-km optically amplified links is realized based on the series structure of multiple PM. Reducing the mesoscopic power of the ciphertext quantum state can improve the security level of QNRC system, but it will damage the transmission performance of the system at the same time. It is very important to select the appropriate mesoscopic power to optimize the security and reliability of QNRC system.
Recent progress in quantum technologies has brought quantum communication and networking from a largely theoretical idea to an emerging practical reality. By exploiting fundamental quantum phenomena such as superposition and entanglement, quantum communication promises capabilities that are fundamentally different and out of reach for classical communication systems, particularly in terms of security and information sharing. This review aims to present the essential theoretical concepts required to understand quantum communication, alongside an experimental and engineering perspective that highlights how these ideas are realized using real hardware. We explain core principles and protocols in a manner that connects the physics to practical system design, allowing readers to see how quantum theory and communication technology jointly enable quantum networking. The paper further surveys recent experimental and technological advances that have made practical quantum communication possible, emphasizing the role of photonic hardware, sources, detectors, and integrated platforms in enabling key operations, now leading to deployment of multi-node long-distance quantum networks. Finally, we also present the current developments in quantum-secure communication and quantum networking efforts undergoing in India, placing them in the context of the global progress.