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Side-channel free quantum digital signature with source monitoring

Chinese Physics B 2025年第1期34卷 53-58页

作者： Luo-Jia Ma Ming-Shuo Sun Chun-Hui Zhang Hua-Jian Ding Xing-Yu Zhou Jian Li Qin Wang Institute of Quantum Information and Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Broadband Wireless Communication and Sensor Network Technology Key Laboratory of Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China

Quantum digital signature(QDS)can guarantee the information-theoretical security of a signature with the fundamental laws of quantum ***,most current QDS protocols do not take source security into account,leading to an overestimation of the signature *** this paper,we propose to utilize Hong–Ou–Mandel interference to characterize the upper bound of the source imperfections,and further to quantify information leakage from potential ***,we combine decoy-state methods and finite-size analysis in analyzing the signature *** results demonstrate the performance and feasibility of our *** current work can improve the practical security of QDS systems,thereby promoting their further networked applications.

关键词： Hong-Ou-Mandel interference side-channel free quantum digital signature

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Improved reference-frame-independent quantum key distribution with intensity fluctuations

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Chinese Physics B 2025年第2期34卷 48-52页

作者： Zi-Qi Chen Hao-Bing Sun Ming-Shuo Sun Qin Wang Institute of Quantum Information and Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Broadband Wireless Communication and Sensor Network Technology Key Laboratory of Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China

Reference-frame-independent quantum key distribution(RFI-QKD) can avoid real-time calibration operation of reference frames and improve the efficiency of the communication process. However, due to imperfections of optical devices,there will inevitably exist intensity fluctuations in the source side of the QKD system, which will affect the final secure key rate. To reduce the influence of intensity fluctuations, an improved 3-intensity RFI-QKD scheme is proposed in this *** considering statistical fluctuations and implementing global parameter optimization, we conduct corresponding simulation analysis. The results show that our present work can present both higher key rate and a farther transmission distance than the standard method.

关键词： quantum key distribution intensity fluctuations decoy-state method

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Equivalent Bandwidth Concept and Its Usage in the network Selection

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China communications 2025年第2期22卷 213-225页

作者： Ma Anhua Pan Su Zhou Weiwei Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts and TelecommunicationsNanjing 210003China

Maximize the resource utilization efficiency and guarantee the quality of service(QoS)of users by selecting the network are the key issues for heterogeneous network operators,but the resources occupied by users in different networks cannot be compared *** paper proposes a network selection algorithm for heterogeneous ***,the concept of equivalent bandwidth is proposed,through which the actual resources occupied by users with certain QoS requirements in different networks can be compared *** the concept of network applicability is defined to express the abilities of networks to support different *** proposed network selection algorithm first evaluates whether the network has enough equivalent bandwidth required by the user and then prioritizes network with poor applicability to avoid the situation that there are still residual resources in entire network,but advanced services can not be *** simulation results show that the proposed algorithm obtained better performance than the baselines in terms of reducing call blocking probability and improving network resource utilization efficiency.

关键词： call blocking probability equivalent bandwidth heterogeneous network network applicability

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A teacher-student based attention network for fine-grainedimage recognition

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Digital communications and networks 2025年第1期11卷 52-59页

作者： Ang Li Xueyi Zhang Peilin Li Bin Kang Key Laboratory of Broadband Wireless Communication and Sensor Network Technology(Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing210003China School of Communications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing210003China School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing210003China

Fine-grained Image Recognition(FGIR)task is dedicated to distinguishing similar sub-categories that belong to the same super-category,such as bird species and car *** order to highlight visual differences,existing FGIR works often follow two steps:discriminative sub-region localization and local feature ***,these works pay less attention on global context *** neglect a fact that the subtle visual difference in challenging scenarios can be highlighted through exploiting the spatial relationship among different subregions from a global view ***,in this paper,we consider both global and local information for FGIR,and propose a collab.rative teacher-student strategy to reinforce and unity the two types of *** framework is implemented mainly by convolutional neural network,referred to Teacher-Student Based Attention Convolutional Neural network(T-S-ACNN).For fine-grained local information,we choose the classic Multi-Attention network(MA-Net)as our baseline,and propose a type of boundary constraint to further reduce background noises in the local attention *** this way,the discriminative sub-regions tend to appear in the area occupied by fine-grained objects,leading to more accurate sub-region *** fine-grained global information,we design a graph convolution based Global Attention network(GA-Net),which can combine extracted local attention maps from MA-Net with non-local techniques to explore spatial relationship among *** last,we develop a collab.rative teacher-student strategy to adaptively determine the attended roles and optimization modes,so as to enhance the cooperative reinforcement of MA-Net and *** experiments on CUB-200-2011,Stanford Cars and FGVC Aircraft datasets illustrate the promising performance of our framework.

关键词： Fine-grained image recognition Collab.rative teacher-student strategy Multi-attention Global attention

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Optimized Qubit -Based Synchronization in Quantum key Distribution

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IEEE communications Letters 2025年第5期29卷 1087-1091页

作者： Sun, Hao-Bing Li, Jian Chu, Xing-Wang Liu, Jing-Yang Ding, Hua-Jian Wang, Qin Nanjing University of Posts and Telecommunications Institute of quantum information and technology Broadband Wireless Communication and Sensor Network Technology Key Lab of Ministry of Education Telecommunication and Networks National Engineering Research Center Nanjing210003 China

Quantum key distribution (QKD) enables the generation of information-theoretic secure keys between two remote parties. A critical component of successful QKD implementation is the effective synchronization of clocks between these users. Traditional methods of locking to a reference clock or transmitting a synchronization signal rely on auxiliary equipment, which increases the complexity and cost, thus hindering the widespread deployment of QKD. Here, we propose a method to achieve clock and pulse synchronization by exploiting a subset of the transmitted qubits. We demonstrate our scheme with a time-bin phase-coding BB84 QKD system and verify the realization of long-term stable key generation over distances of 50 km and 100 km. Our method simplifies the implementation of QKD systems and introduces new possibilities for synchronization algorithms in other quantum communication protocols. © 1997-2012 IEEE.

关键词： Qubits

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Physical Layer Security for Friendly Jammers Assisted Satellite-Terrestrial Integrated networks

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IEEE Internet of Things Journal 2025年

作者： Cao, Weifeng Zou, Yulong Li, Bin Zhu, Jia Nanjing Institute of Technology School of Automation Nanjing211167 China NUPT School of Telecommunications and Information Engineering Nanjing210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology China

This paper investigates the physical layer security (PLS) of a satellite-terrestrial integrated network (STIN) consisting of a satellite (S), a destination (D), and several friendly jammers in the presence of an eavesdropper (E). For improving PLS of the STIN, we propose three friendly jammer assisted communication schemes to help S securely send confidential information to D, i.e., the random jammer selection assisted communication (RJSC) scheme, the optimal jammer selection assisted communication (OJSC) scheme, and the multiple jammers assisted communication (MJC) scheme. For performance comparison, the non-jammer assisted communication (NJC) scheme is also presented. We analyze secrecy performance of the NJC, RJSC, OJSC, and MJC schemes by carrying out their closed-form secrecy outage probability (SOP) expressions, respectively. Numerical results unveil that the RJSC, OJSC, and MJC schemes exceed the NJC scheme with regard to their SOPs (e.g., as shown in Fig. 2, when the signal-to-noise ratio is 25 dB, SOP of the STIN drops from 70% to 3%), and the OJSC scheme can get the best secrecy performance, showing the secrecy benefits of adopting friendly jammers assisted communication schemes against eavesdropping. Additionally, by increasing the number of friendly jammers, the secrecy performance of the OJSC and MJC schemes can be significantly enhanced, while that of the RJSC scheme remains unchanged. © 2014 IEEE.

关键词： Jamming

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communication-Efficient Distributed Learning in Massive IoT: A Graph-Based Perspective

Communication-Efficient Distributed Learning in Massive IoT:...

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IEEE Conference on wireless communications and networking

作者： Lindong Zhao Jingyue Tang Mingzhe Chen Liang Zhou Weihua Zhuang Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Various distributed learning approaches emerge for enabling ubiquitous intelligence in Internet of Things (IoT) without sacrificing data privacy. To improve communication efficiency in frequent knowledge exchange over resource-constrained IoT, different techniques for client selection have been proposed. However, the intractable scalab.lity issues remain to be addressed in massive IoT, since highly-coupled co-channel interference adds exponential complexity to combinatorial client selection. In this work, we develop a client selection framework highly-scalab.e to large-scale networks with thousands of devices, which exploits the inherent graph structure derived from knowledge exchange and co-channel interference. Specifically, we first model a client selection problem for jointly optimizing learning performance and system cost under volatile network conditions. The formulated problem is encoded into a node classification problem by a directed graph. Subsequently, a general yet simple solver is designed based on graph neural networks, which selects clients by classifying node status with recursive neighborhood aggregation of node representations. Finally, extensive experimental results demonstrate that the proposed approach can perform on par with state-of-the-art methods, while scaling to networks whose size is orders of magnitude larger than they can handle.

关键词： Performance evaluation Knowledge engineering Computer aided instruction Costs Distance learning Scalab.lity Graph neural networks Data models Internet of Things Interchannel interference

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Multi-Modal Sensing and Lighting Estimation for PoE-Enabled Intelligent and Energy-Efficient Lighting networks

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IEEE Internet of Things Journal 2025年

作者： Tang, Liwei Xu, Yuanyuan Liu, Xiaodong Wang, Yuhao Wang, Jinyuan Shao, Huilong Nanchang University School of Information Engineering Nanchang330031 China Nanchang Laboratory Nanchang330224 China Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China

The application of power over Ethernet (PoE)-enabled lighting has emerged as a groundbreaking technology with the potential to achieve cooperative control and create an energy-saving lighting network. However, fine-grained user-side lighting environment perception is crucial to improve energy efficiency and user experience. To tackle this issue, a PoE-enabled intelligent lighting network with multi-modal sensing is proposed. Specifically, a multi-modal sensor is designed and installed on the side of the luminaire to provide both fine-grained lighting environment monitor and dimming. Then, a multilayer perceptron (MLP)-based estimation scheme is proposed to estimate the illumination and color temperature information around the user activity area. Moreover, an experimental lighting network is constructed and deployed in a classroom to measure practical lighting dataset. The proposed scheme effectively estimates the lighting quality on the user side based on the measurement data. Furthermore, based on the estimated information and the collab.rative control capabilities of PoE, the operating current of the luminaire is updated in real time, and thus the ambient light resource is fully utilized. Finally, the proposed lighting network achieves a 39.99% energy saving. © 2014 IEEE.

关键词： Lighting fixtures

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Cross-Modal Haptic Generation for Emergency Rescue in Internet of Robotic Things

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IEEE Internet of Things Journal 2025年

作者： Liu, Hengfa Wei, Xin Gao, Yun Zhou, Liang Qian, Yi Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing210003 China University of Nebraska-Lincoln Department of Electrical and Computer Engineering OmahaNE68588 United States

Robots equipped with multi-modal sensing capabilities play an important role in the Internet of Robotic Things (IoRT), especially in emergency rescue. However, existing rescue robots pose challenges for human operators in achieving precise manipulation due to the absence of haptic signals. Additionally, limited and fluctuating bandwidth in emergency rescue renders current cross-modal haptic generation schemes ineffective. To overcome this dilemma, we propose a novel cross-modal haptic generation scheme that enhances scalab.lity across diverse network conditions by leveraging correlations among audio-visual-haptic modalities. Specifically, we first propose an edge-device collab.ration-based architecture that dynamically extracts semantics from audio-visual signals, tailored to the current network conditions, for haptic generation. This is achieved by predicting the network state at the edge and performing multi-modal encoding and fusion at the device. Next, we design a scalab.e cross-modal haptic generation scheme that implements the optimal generation strategy based on received audio-visual semantics of different granularities, ensuring real-time acquisition of coarse-grained or fine-grained haptic feedback. Finally, numerical experimental results conducted on a multi-modal dataset and a simulated emergency environment indicate that the proposed scheme reliably generates haptic signals in emergency rescue. © 2025 IEEE.

关键词： Robots

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Cross-Modal Haptic Compression Inspired by Embodied AI for Haptic communications

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IEEE Transactions on Multimedia 2025年

作者： Lu, Hang Tan, Xinmeng Chen, Mingkai Zhang, Zhe Zhang, Xuguang Chen, Jianxin Wei, Xin Zhao, Tiesong Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology China Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Fuzhou University Fujian Science & Technology Innovation Laboratory for Optoelectronic Information Fuzhou350108 China

Haptic data compression has gradually become a key issue for emerging real-time haptic communications in Tactile Internet (TI). However, it is challenging to achieve a tradeoff between high perceptual quality and compression ratio in haptic data compression scheme. Inspired by the perspective of embodied AI, we propose a cross-modal haptic compression scheme for haptic communications to improve the perception quality on TI devices in this paper. Since multimodal fusion is routinely employed to improve the ability of system in cognition, we assume that haptic codec is guided by visual semantics to optimize parameter settings in the coding process. We first design a multi-dimensional tactile feature fusion network (MTFFN) relying on multi-head attention mechanism. The MTFFN extracts the multi-dimensional features from the material surface and maps them to infer the coding parameters. Secondly, we provide second-order difference and linear interpolation to establish an criterion for the determination of optimal codec parameters, which are customized by the material categories so as to give high robustness. Finally, the simulation results reveal that our compression scheme can efficiently make a personalized codec procedure for different materials, obtaining more than 17% improvement in terms of compression ratio with high perceptual quality at the same time. © 2025 IEEE.

关键词： Data compression ratio

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