IET Quantum Communication最新文献

SARS-CoV-2 epidemic (severe acute respiratory corona virus 2 syndromes) has caused major impacts on a global scale. Several countries, including India, Europe, U.S.A., introduced a full state/nation lockdown to minimise the disease transmission through human interaction after the virus entered the population and to minimise the loss of human life. Millions of people have gone unemployed due to lockdown implementation, resulting in business and industry closure and leading to a national economic slowdown. Therefore, preventing the spread of the COVID-19 virus in the world while also preserving the global economy is an essential problem requiring an effective and immediate solution. Using the compartmental epidemiology S, E, I, R or D (Susceptible, Exposed, Infectious, Recovery or Death) model extended to multiple population regions, the authors predict the evolution of the SARS-CoV-2 disease and construct an optimally scheduled lockdown calendar to execute lockdown over phases, using the well-known Knapsack problem. A comparative analysis of both classical and quantum models shows that our model decreases SARS-CoV-2 active cases while retaining the average global economic factor, Gross Domestic Product, in contrast to the scenario with no lockdown.

Quantum-based technologies will provide system engineers with new capabilities for securing data communications. The UK AirQKD project has implemented a Free-Space Optical Quantum Key Distribution (QKD) system to enable the continuous generation of symmetric encryption keys. One of the use cases for the generated keys is to secure Vehicle-to-Everything (V2X) communications. V2X applications would benefit from the certificate-free security provided by QKD for a post-quantum society. How FSO-QKD could integrate into a V2X architecture is examined. An overview of V2X is provided with the role that FSO-QKD could secure V2X data though some obstacles exist. One of the issues with 6G communications is the potential line-of-sight (LOS) considerations between the V2X devices. The modelling required for LOS is examined to analyse the outage performance of the building to infrastructure links in the 6G architecture. The results from the model show that further work is required if 6G LOS communications are going to be relied upon for future safety-critical V2X applications.

The authors devised a protocol that allows two parties, who may malfunction or intentionally convey incorrect information in communication through a quantum channel, to verify each other's measurements and agree on each other's results. This has particular relevance in a modified version of the quantum coin flipping game. The key innovation of the authors’ work includes the new design of a quantum coin that excludes any advantage of cheating, by which the long-standing problem of the fair design of the game is, affirmatively, solved. Furthermore, the analysis is extended to N-parties communicating with each other, where multiple solutions for the verification of each player's measurement is proposed. The results in the N-party scenario could have particular relevance for the implementation of future quantum networks, where verification of quantum information is a necessity.

Quasi-chaotic generators are used for producing a pseudorandom behaviour that can be used for encryption/decryption and secure communications, introducing an implementation of them based on quantum technology. Namely, the authors propose a quasi-chaotic generator based on quantum modular addition and quantum modular multiplication and they prove that quantum computing allows the parallel processing of data, paving the way for a fast and robust multi-channel encryption/decryption scheme. The resulting structure is validated by means of several experiments, which assessed the performance with respect to the original VLSI solution and ascertained the desired noise-like behaviour.

As past works have shown, information-theoretically secure implementations transmitters of Y00 quantum noise randomised cypher are possible. An advance to the provably secure Y00 protocol by bridging gaps between experimental results and theoretical analyses under so-called quantum collective measurement attacks with known plaintexts is aimed. It would be the strongest attack on the Y00 protocol in the context of quantum key distribution protocols. However, recently proposed security evaluations under the attacks were too abstract to apply to experiments. Therefore, security analyses directly evaluable with the equipped Y00 transmitters under attack are offered. Thus, new security indices are proposed instead of ordinary security measures, such as the bit-error-rate guarantee between optical signals or a masking size. Contrarily, unsolved problems are also listed.

In quantum key distribution-secured optical networks (QKD-ONs), constrained network resources limit the success probability of QKD lightpath requests (QLRs). Thus, the selection of an appropriate route and the efficient utilisation of network resources for establishment of QLRs are the essential and challenging problems. This work addresses the routing and resource assignment (RRA) problem in the quantum signal channel of QKD-ONs. The RRA problem of QKD-ONs is a complex decision making problem, where appropriate solutions depend on understanding the networking environment. Motivated by the recent advances in deep reinforcement learning (DRL) for complex problems and also because of its capability to learn directly from experiences, DRL is exploited to solve the RRA problem and a DRL-based RRA scheme is proposed. The proposed scheme learns the optimal policy to select an appropriate route and assigns suitable network resources for establishment of QLRs by using deep neural networks. The performance of the proposed scheme is compared with the deep-Q network (DQN) method and two baseline schemes, namely, first-fit (FF) and random-fit (RF) for two different networks, namely The National Science Foundation Network (NSFNET) and UBN24. Simulation results indicate that the proposed scheme reduces blocking by 7.19%, 10.11%, and 33.50% for NSFNET and 2.47%, 3.20%, and 19.60% for UBN24 and improves resource utilisation up to 3.40%, 4.33%, and 7.18% for NSFNET and 1.34%, 1.96%, and 6.44% for UBN24 as compared with DQN, FF, and RF, respectively.

In this article, a protocol for information lossless teleportation using W states is proposed. Firstly, the information lossless teleportation of an unknown state with a maximally entangled W-state channel, which protects the original unknown state information even in case of teleportation failure is investigated. Next, we generalise our scheme to non-maximally entangled W-state channels. Finally, the principle of the proposed scheme is validated by performing experiments on the quantum circuit simulator Quirk. Our study shows that W states can be used to teleport any quantum state without information loss through single-qubit measurements and local unitary operations.

This paper applies a quantum machine learning technique to predict mobile users' trajectories in mobile wireless networks by using an approach called quantum reservoir computing (QRC). Mobile users' trajectories prediction belongs to the task of temporal information processing, and it is a mobility management problem that is essential for self-organising and autonomous 6G networks. Our aim is to accurately predict the future positions of mobile users in wireless networks using QRC. To do so, the authors use a real-world time series dataset to model mobile users' trajectories. The QRC approach has two components: reservoir computing (RC) and quantum computing (QC). In RC, the training is more computational-efficient than the training of simple recurrent neural networks since, in RC, only the weights of the output layer are trainable. The internal part of RC is what is called the reservoir. For the RC to perform well, the weights of the reservoir should be chosen carefully to create highly complex and non-linear dynamics. The QC is used to create such dynamical reservoir that maps the input time series into higher dimensional computational space composed of dynamical states. After obtaining the high-dimensional dynamical states, a simple linear regression is performed to train the output weights and, thus, the prediction of the mobile users' trajectories can be performed efficiently. In this study, we apply a QRC approach based on the Hamiltonian time evolution of a quantum system. The authors simulate the time evolution using IBM gate-based quantum computers, and they show in the experimental results that the use of QRC to predict the mobile users' trajectories with only a few qubits is efficient and can outperform the classical approaches such as the long short-term memory approach and the echo-state networks approach.

In the technologically changing world, the demand for ultra-reliable, faster, low power, and secure communication has significantly risen in recent years. Researchers have shown immense interest in emerging quantum computing (QC) due to its potentials of solving the computing complexity in the robust and efficient manner. It is envisioned that QC can act as critical enablers and strong catalysts to considerably reduce the computing complexities and boost the future of sixth generation (6G) and beyond communication systems in terms of their security. In this study, the fundamentals of QC, the evolution of quantum communication that encompasses a wide spectrum of technologies and applications and quantum key distribution, which is one of the most promising applications of quantum security, have been presented. Furthermore, various parameters and important techniques are also investigated to optimise the performance of 6G communication in terms of their security, computing, and communication efficiency. Towards the end, potential challenges that QC and quantum communication may face in 6G have been highlighted along with future directions.

Secure Multiparty Computation (SMC) enables multiple parties to cooperate securely without compromising their privacy. SMC has the potential to offer solutions for privacy obstacles in vehicular networks. However, classical SMC implementations suffer from efficiency and security challenges. To address this problem, two quantum communication technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution were utilised. These technologies supply symmetric and oblivious keys respectively, allowing fast and secure inter-vehicular communications. These quantum technologies are integrated with the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol to form a Quantum Secure Multiparty Computation (QSMC) platform. A lane change service is implemented in which vehicles broadcast private information about their intention to exit the highway. The proposed QSMC approach provides unconditional security even against quantum computer attacks. Moreover, the communication cost of the quantum approach for the lane change use case has decreased by 97% when compared to the classical implementation. However, the computation cost has increased by 42%. For open space scenarios, the reduction in communication cost is especially important, because it conserves bandwidth in the free-space radio channel, outweighing the increase in computation cost.