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Decoy-state quantum-key-distribution-based quantum private query with error tolerance bound

Physical Review A 2024年第5期109卷 052442-052442页

作者： Bin Liu Zhonghao Liang Wei Huang Fei Gao Jiayi Yuan Bingjie Xu College of Computer Science The State Key Laboratory of Networking and Switching Technology Center for Network and Information Science and Technology on Communication Security Laboratory Institute of Southwestern Communication Chengdu 610041 China

Quantum private query (QPQ) faces many challenges in practical applications. At present, some scholars have made substantial work on overcoming channel loss, channel noise, and nonideal light sources, respectively. However, a protocol that would overcome all three of these problems has yet to materialize. We review a practical QPQ protocol that can actually work in noisy channels. This protocol has an upper bound on tolerable errors based on the required level of security and reliability. Then, we study the security of the above QPQ protocol under weak coherent pulses. The results indicate that the multiphoton pulses have induced significant vulnerabilities, which seriously threatens the privacy of users. Finally, we propose a decoy-state method to solve the serious threat to user security caused by multiphoton pulses. The analysis shows that the decoy-state method significantly improves the security of the QPQ protocol under weak coherent pulses. The improved protocol can not only tolerate transmission losses and channel noise, but also overcome the security vulnerability caused by a nonideal light source.

关键词： Quantum communication Quantum error correction Quantum information theory Quantum protocols Quantum state transfer

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Two-layer Lagrange-based relay network topology and trajectory design for solar system explorations

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Science China(Information Sciences) 2024年第6期67卷 342-358页

作者： Jun CAO Jian JIAO Hao LIU Rongxing LU Qinyu ZHANG Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Harbin Institute of Technology (Shenzhen) Faculty of Computer Science (FCS) University of New Brunswick

Exploration targeting outer planets and even the edge of the solar system is an emerging direction for the deep-space exploration in the next decades. To address this challenge, a novel two-layer Lagrangebased relay network topology is proposed in this study. Specifically, we utilize the Sun-Mars and Sun-Saturn Lagrange points(LPs) L4 and L5 to build a two-layer backbone relay network, which ensures continuous and high-efficiency communication capability for the exploration of the solar system. Furthermore, we utilize the planetary gravity assist and design the transfer trajectory of backbone relays with the help of planetary celestial body motion equations and Kepler's laws. Moreover, we conduct link budget analysis for multihop relay transmission under Gamma-Gamma distribution, shadowed Rician fading, and additive white Gaussian noise channels in several typical exploration scenarios and validate that the LP relays can effectively support future deep-space exploration missions.

关键词： deep-space communication Lagrangian points backbone relay network transfer trajectory relay selection

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Mobility-Aware Multi-Task Migration and Offloading Scheme for Internet of Vehicles

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Chinese Journal of Electronics 2023年第6期32卷 1192-1202页

作者： LI Xujie TANG Jing XU Yuan SUN Ying College of Computer and Information Hohai University State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Key Lab for Wireless Sensor Network and Communication Shanghai Institute of Microsystem School of Information Engineering Jiangsu Open University

In Internet of vehicles, vehicular edge computing(VEC) as a new paradigm can effectively accomplish various tasks. Due to limited computing resources of the roadside units(RSUs), computing ability of vehicles can be a powerful supplement to computing resources. Then the task to be processed in data center can be offloaded to the vehicles by the RSUs. Due to mobility of the vehicles, the tasks will be migrated among the RSUs. How to effectively offload multiple tasks to the vehicles for processing is a challenging problem. A mobility-aware multi-task migration and offloading scheme for Internet of vehicles is presented and analyzed. Considering the coupling between migration and offloading, the joint migration and offloading optimization problem is formulated. The problem is a NP-hard problem and it is very hard to be solved by the conventional methods. To tackle the difficult problem, the idea of alternating optimization and divide and conquer is introduced. The problem can be decoupled into two sub-problems: computing resource allocation problem and vehicle node selection problem. If the vehicle node selection is given, the problem can be solved based on Lagrange function. And if the allocation of computing resource is given, the problem turns into a 0-1 integer programming problem, and the linear relaxation of branch bound algorithm is introduced to solve it. Then the optimization value is obtained through continuous iteration. Simulation results show that the proposed algorithm can effectively improve system performance.

关键词： Costs Computational modeling System performance Simulation Programming Multitasking Resource management

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Barycenter Calibration for MUSIC Spectrum of OFDM-ISAC Signals – A Super-Resolution Waveform Perspective 14th

Barycenter Calibration for MUSIC Spectrum of OFDM-ISAC Sig...

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14th EAI International Conference on Wireless and Satellite Systems, WiSATS 2024

作者： Yin, Meiyu Li, Jingwen Gong, Jialong Liu, Xiqing Peng, Mugen Xia, Nian State Key Laboratory of Networking and Switching Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China School of Computer and Electronic Information/School of Artificial Intelligence Nanjing Normal University Nanjing210023 China

ISBN: (纸本)9783031862021

The sixth-generation mobile communication system is expected to provide sensing services, and thus the integrated sensing and communication waveform has emerged as a hot research topic. In typical sensing systems, such as radar, sensing resolution is often constrained by available wireless resources. Achieving super-resolution sensing within the resource constraint poses a significant challenge. To this end, this work proposed a calibration algorithm for orthogonal frequency division multiplexing waveforms to conduct barycenter calibration (BC) of the multiple signal classification (MUSIC) spectrum that performs two-dimensional sensing. Simulation results demonstrated that the BC algorithm could significantly reduce sensing errors. Even at the edge of the MUSIC spectrum, it still exhibits robust performance. In addition, to comprehensively evaluate the performance gains, we introduce the capacity-to-error ratio and provide simulation results and discussions. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Orthogonal frequency division multiplexing

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Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

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Science China(Information Sciences) 2023年第3期66卷 7-25页

作者： Guangxu ZHU Zhonghao LYU Xiang JIAO Peixi LIU Mingzhe CHEN Jie XU Shuguang CUI Ping ZHANG Shenzhen Research Institute of Big Data Future Network of Intelligence Institute (FNii) The Chinese University of Hong Kong (Shenzhen) School of Science and Engineering (SSE) The Chinese University of Hong Kong (Shenzhen) State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.

关键词： sixth-generation (6G) edge intelligence artificial intelligence of things (AIoT) integrated sensing communication and computation (ISCC)

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Edge-Driven Industrial Computing Power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

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Stochastic Geometry Based Performance Analysis of Terrestrial-to-Aerial Networks for Nomadic communications

Stochastic Geometry Based Performance Analysis of Terrestria...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Dong, Wen-Yu Yang, Shaoshi Lin, Wei Zhao, Wei Gui, Jia-Xing Zhang, Ping Chen, Sheng The School of Information and Communication Engineering Beijing University of Posts and Telecommunications China The Key Laboratory of Universal Wireless Communications Ministry of Education China The State Key Laboratory of Networking and Switching Technology Beijing100876 China University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

ISBN: (纸本)9798350351255

In this paper, we propose a stochastic geometry based innovative model to characterize the impact of the limited-size distribution region of terrestrial terminals in terrestrial-to-aerial networks by jointly using a binomial point process (BPP) and a type-II Matérn hard-core point process (MHCPP). Then, we analyze the relationship between the spatial distribution of the coverage areas of aerial nodes and the limited-size distribution region of terrestrial terminals, thereby deriving the distance distribution of the terrestrial-aerial (T-A) links. Furthermore, we consider the stochastic nature of the spatial distributions of terrestrial terminals and unmanned aerial vehicles (UAVs), and conduct a thorough analysis of the coverage probability of the T-A links under Nakagami fading. Finally, the accuracy of our theoretical derivations are confirmed by Monte Carlo simulations. Our research offers fundamental insights into the system-level performance optimization for the realistic terrestrial-to-aerial networks involving nomadic aerial base-stations and terrestrial terminals confined in a limited-size region. © 2024 IEEE.

关键词： Stochastic systems

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Outage Probability Analysis of Uplink Heterogeneous Non-terrestrial Networks: A Novel Stochastic Geometry Model

Outage Probability Analysis of Uplink Heterogeneous Non-terr...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Dong, Wen-Yu Yang, Shaoshi Lin, Wei Zhao, Wei Gui, Jia-Xing Chen, Sheng Beijing University of Posts and Telecommunications School of Information and Communication Engineering China Ministry of Education Key Laboratory of Universal Wireless Communications China State Key Laboratory of Networking and Switching Technology Beijing100876 China University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

ISBN: (纸本)9798350351255

In harsh environments such as mountainous terrain, dense vegetation areas, or urban landscapes, a single type of unmanned aerial vehicles (UAVs) may encounter challenges like flight restrictions, difficulty in task execution, or increased risk. Therefore, employing multiple types of UAVs, along with satellite assistance, to collaborate becomes essential in such scenarios. In this context, we present a stochastic geometry based approach for modeling the heterogeneous non-terrestrial networks (NTNs) by using the classical nbinomial point process and introducing a novel point process, called Matérn hard-core cluster process (MHCCP). Our MHCCP possesses both the exclusivity and the clustering properties, thus it can better model the aircraft group composed of multiple clusters. Then, we derive closed-form expressions of the outage probability (OP) for the uplink (aerial-to-satellite) of heterogeneous NTNs. Unlike existing studies, our analysis relies on a more advanced system configuration, where the integration of beamforming and frequency division multiple access, and the shadowed-Rician (SR) fading model for interference power, are considered. The accuracy of our theoretical derivation is confirmed by Monte Carlo simulations. Our research offers fundamental insights into the system-level performance optimization of NTNs. © 2024 IEEE.

关键词： Stochastic systems

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Distributed Semisupervised Partial Label Learning over Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第3期3卷 414-425页

作者： Liu, Ying Xu, Zhen Zhang, Chen Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang University Zhejiang Key Laboratory of Information Processing Communication and Networking Hangzhou310027 China Wenzhou University College of Computer Science and Artificial Intelligence Engineering Wenzhou325035 China

Partial label learning (PLL) deals with the classification from sufficient training data associated with a candidate set of labels but not the only correct one. In this article, we focus on PLL with some ambiguously labeled and many unlabeled data collected from multiple nodes distributed over a network. To solve this problem, a distributed semisupervised PLL (dS2PLL) framework is formulated, in which the weighted logistic loss with respect to partially labeled (PL) and unlabeled data is utilized. In the proposed dS^2PLL algorithm, the parameters of the classifier are adapted in a collaborative manner, meanwhile the weights of each training sample and the ground-truth confidence of candidate labels are adaptively learned to disambiguate the correct label from the candidate label set. The performance of the proposed algorithm is analyzed theoretically and verified by simulations on both synthetic and real datasets. Results show that the proposed algorithm achieves good classification performance and robustness to the ambiguity in the labels. © 2020 IEEE.

关键词： Classification (of information)

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On the Performance of Joint Resource Allocation and Control in Industrial IoT

On the Performance of Joint Resource Allocation and Control ...

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2023 IEEE/CIC International Conference on communications in China, ICCC 2023

作者： Wang, Ying Wu, Shaohua Jiao, Jian Zhang, Ning Zhang, Qinyu The Department of Electronics and Information Engineering Shenzhen518055 China The Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Shenzhen518055 China Peng Cheng Laboratory Shenzhen518055 China University of Windsor Department of Electrical and Computer Engineering WindsorONN9B 3P4 Canada

ISBN: (纸本)9798350345384

In this paper, a wireless networked control system with a local controller and remote controller is investigated. The observed states can be controlled directly by the local controller or controlled by the remote controller via an unreliable channel. In this scenario, we focus on a more realistic problem that the network might be faced with, that is, the lifespan of the network. However, this issue has received little attention. The lifespan of the network is considered in two-folds: 1) a stochastic sample and transmission scheme is adopted to reduce the power consumption and 2) the transmit power is optimized to guarantee the total transmission power limitation. In order to balance the control performance and the network lifespan, an optimization problem on communication and control co-design is formulated. In particular, we aim to jointly optimize the resource allocation and local/remote controls by minimizing the linear quadratic regulation (LQR) control cost under the constraints of transmit power and transmission probability. The results of the considered optimization problem show that there exists an optimal transmit power and the corresponding transmission probability that can minimize the control cost function. Numerical results are further provided to verify the theoretical analysis. © 2023 IEEE.

关键词： Resource allocation

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