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An efficient quantum proactive incremental learning algorithm

Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 45-53页

作者： Lingxiao Li Jing Li Yanqi Song Sujuan Qin Qiaoyan Wen Fei Gao state key laboratory of networking and switching technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing 100876China

In scenarios where a large amount of data needs to be learned,incremental learning can make full use of old knowledge,signif-icantly reduce the computational cost of the overall learning process,and maintain high *** this paper,taking the MaxCut problem as our example,we introduce the idea of incremental learning into quantum computing,and propose a Quantum Proactive Incremental Learning algorithm(QPIL).Instead of a one-off training of quantum circuit,QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices,proactively reducing large-scale problems to smaller ones to solve in steps,providing an efficient solution for ***,some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at ***,in each incremental phase,the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current *** perform experiments on 120 different small-scale graphs,and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR),time cost,anti-forgetting,and solv-ing *** particular,QPIL’s AR surpasses 20%of mainstream quantum baselines,and the time cost is less than 1/5 of *** idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale MaxCut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training MaxCut quantum computing

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Energy Consumption Minimization for NOMA-Based Secure UAV-MEC Network

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China Communications 2025年第03期 202-216页

作者： Zhang Hao Huang Yuzhen Zhang Zhi Lu Xingbo School of Information and Communication Engineering Beijing University of Posts and Telecommunications state key laboratory of networking and switching technology Beijing University of Posts and Telecommunications The Academy of Military Sciences of PLA

Applying non-orthogonal multiple access(NOMA) to the mobile edge computing(MEC) network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving computing resource constraints and coverage problems. However,the UAV-enabled network has a serious risk of information leakage on account of the openness of wireless channel. This paper considers a UAV-MEC secure network based on NOMA technology, which aims to minimize the UAV energy consumption. To achieve the purpose while meeting the security and users' latency requirements, we formulate an optimization problem that jointly optimizes the UAV trajectory and the allocation of network resources. Given that the original problem is non-convex and multivariate coupled, we proposed an effective algorithm to decouple the nonconvex problem into independent user relation coefficients and subproblems based on successive convex approximation(SCA) and block coordinate descent(BCD). The simulation results showcase the performance of our optimization scheme across various parameter settings and confirm its superiority over other benchmarks with respect to energy consumption.

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Endogenous Security Through AI-Driven Physical-Layer Authentication for Future 6G Networks

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ZTE Communications 2025年

作者： MENG Rui FAN Dayu XU Xiaodong LYU Suyu TAO Xiaofeng state key laboratory of networking and switching technology， Beijing University of Posts and Telecommunications Department of Broadband Communication，Peng Cheng laboratory School of Information Science and technology， Beijing University of technology National Engineering laboratory for Mobile Network Technologies， Beijing University of Posts and Telecommunications

The 6G mobile networks are expected to offer higher data rates， spectral efficiency， and reliability than 5G， achieving a significant transition from mobile communication to mobile information services. However， the revolutionary network architecture and emerging enabling technologies of 6G will bring increasingly severe security challenges. To ensure the access security of 6G， physical-layer authentication (PLA) leverages the randomness and space-time-frequency uniqueness of the channel to provide unique identity signatures for transmitters. Furthermore， the introduction of artificial intelligence (AI) facilitates the learning of the distribution characteristics of channel fingerprints， effectively addressing the uncertainties and unknown dynamic challenges in the process of wireless link modeling. This paper reviews representative AI-enabled PLA schemes and proposes a graph neural network (GNN)-based PLA approach in response to the challenges faced by existing methods in identifying mobile users. Simulation results demonstrate that the proposed method outperforms six baseline schemes in terms of authentication accuracy. Furthermore， this paper outlines the future development directions of PLA.

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Achievable Rate Analysis and Optimization of Double-RIS Assisted Spatially Correlated MIMO with Statistical CSI

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China Communications 2025年第1期22卷 139-157页

作者： Xu Kaizhe Guo Jiajia Zhang Jun Jin Shi Ma Shaodan Department of Communications and networking Xi’an Jiaotong-Liverpool UniversitySuzhou 215123China state key laboratory of Internet of Things for Smart City University of MacaoMacao SARChina Jiangsu key laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing 210003China National Mobile Communications Research laboratory Southeast UniversityNanjing 210096China state key laboratory of Internet of Things for Smart City and the Department of Electrical and Computer Engineering University of MacaoMacao SARChina

Reconfigurable intelligent surface(RIS)is a novel meta-material which can form a smart radio environment by dynamically altering reflection directions of the impinging electromagnetic *** the prior literature,the inter-RIS links which also contribute to the performance of the whole system are usually neglected when multiple RISs are *** this paper we investigate a general double-RIS assisted multiple-input multiple-output(MIMO)wireless communication system under spatially correlated non line-of-sight propagation channels,where the cooperation of the double RISs is also *** design objective is to maximize the achievable ergodic rate based on full statistical channel state information(CSI).Specifically,we firstly present a closedform asymptotic expression for the achievable ergodic rate by utilizing replica method from statistical *** a full statistical CSI-enabled optimal design is proposed which avoids high pilot training overhead compared to instantaneous CSI-enabled *** further reduce the signal processing overhead and lower the complexity for practical realization,a common-phase scheme is proposed to design the double *** results show that the derived asymptotic ergodic rate is quite accurate even for small-sized antenna *** the proposed optimization algorithm can achieve substantial gain at the expense of a low overhead and ***,the cooperative double-RIS assisted MIMO framework is proven to achieve superior ergodic rate performance and high communication reliability under harsh propagation environment.

关键词： common reflection pattern double RISs large system analysis MIMO replica method

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Cubature Kalman Fusion Filtering Under Amplify-and-Forward Relays With Randomly Varying Channel Parameters

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 356-368页

作者： Jiaxing Li Zidong Wang Jun Hu Hongli Dong Hongjian Liu the Department of Applied Mathematics Harbin University of Science and Technology IEEE the Department of Computer Science Brunel University London the School of Automation Harbin University of Science and Technology the Artificial Intelligence Energy Research Institute Northeast Petroleum University the Heilongjiang Provincial key laboratory of networking and Intelligent Control Northeast Petroleum University the National key laboratory of Continental Shale Oil of China Northeast Petroleum University the key laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University the School of Mathematics and Physics Anhui Polytechnic University

In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.

关键词： Amplify-and-forward (AaF) relays covariance intersection fusion cubature Kalman filtering multi-sensor systems uniform boundedness

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Domain generalization with semi-supervised learning for people-centric activity recognition

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Science China(Information Sciences) 2025年第1期68卷 171-188页

作者： Jing LIU Wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & technology Fudan University Shanghai East-bund Research Institute on networking Systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial key laboratory of networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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On the feasibility and efficacy of control traffic protection in software-defined networks

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Science China(Information Sciences) 2015年第12期58卷 44-62页

作者： HU YanNan WANG WenDong GONG XiangYang QUE XiRong CHENG ShiDuan state key laboratory of networking and switching technology Beijing University of Posts and Telecommunications

Software Defined networking(SDN) is an emerging networking paradigm that assumes a logically centralized control plane separated from the data plane. Despite all its advantages, separating the control and data planes introduces new challenges regarding resilient communications between the two. That is, disconnections between switches and their controllers could result in substantial packet loss and performance *** paper addresses this challenge by studying the issue of control traffic protection in SDNs with arbitrary numbers of controllers. Specifically, we propose a control traffic protection scheme that combines both local rerouting and constrained reverse path forwarding protections, through which switches can locally react to failures and redirect the control traffic using standby backup forwarding options. Our goal is then to find a set of primary routes for control traffic, called protected control network, where as many switches as possible can benefit from the proposed protection scheme. We formulate the protected control network problem, prove its NP-hardness, and develop an algorithm that reconciles protectability and performance(e.g., switch-to-control latency). Through extensive simulations based on real topologies, we show that our approach significantly improves protectability of control traffic. The results should help further the process of deploying SDN in real-world networks.

关键词： software-defined network protection control traffic resilience optimization

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Blockchain-Based Reliable Fog-Cloud Service Solution for IIoT

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Chinese Journal of Electronics 2021年第2期30卷 359-366页

作者： DAI Meiling XU Siya SHAO Sujie GUO Shaoyong QIU Xuesong XIONG Ao state key laboratory of networking and switching technology Beijing University of Posts and Telecommunications

Industrial Internet of things(IIoT) deploys a large number of smart devices to obtain industrial data, which will be transmitted to cloud for analysis to improve industrial productivity. The management of large-scale devices is complicated, and it's also a challenge to choose a high-quality cloud service for data analysis as the number of service with similar functions increases. To address these issues, we propose a reliable fog-cloud service solution with blockchain-based fog-cloud architecture. In fog layer, we build a management blockchain between fog servers and design a management method for industrial devices; In cloud layer, we construct a service blockchain between cloud service providers to form an open "service market". Quality of service and reputation based matching algorithm and reputation-based consensus algorithm are designed. The simulation results show correctness and efficiency of algorithms, and validate effectiveness of our proposed solution.

关键词： industrial data management blockchain management method large-scale devices reputation-based consensus algorithm data analysis industrial productivity IIoT smart devices industrial devices open service market fog layer matching algorithm cloud computing cloud service providers service blockchain cloud layer high-quality cloud service fog servers fog blockchain-based reliable fog-cloud service solution blockchain-based fog-cloud architecture

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An Isotropic SPPP Model for Femtocells Networks with Outage Probability Constraints

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Chinese Journal of Electronics 2015年第4期24卷 824-831页

作者： ZHANG Jun TIAN Hui state key laboratory of networking and switching technology Beijing University of Posts and Telecommunication

Femtocells have been considered as a costeffective solution to unload traffic from already overburdened macrocell networks in 4G cellular networks. The severe interference in spectrum-sharing macro and femto networks may cause User-equipment(UE) to experience outage. We derive an utmost isotropic Spatial Poisson point process(SPPP) density for Femtocell access points(FAPs) under the UEs’ outage constraints. Based on the derived isotropic SPPP density, we propose a distributed transmit probability self-regulation scheme for an FAP to adapt its transmit probability per Transmission time interval(TTI). The scheme adjusts the homogeneous distributed FAPs in practice deployment to the proposed isotropic one. Simulation results show that the derived density can fulfill the outage probability constraints of UEs while accommodating the maximum femtocells. The selfregulation scheme can adapt the femtocell transmit probabilities to provide reliable downlink service, for even a large number of femtocells per cell site.

关键词： Heterogeneous network Stochastic geometry Outage probability

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