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communication-Efficient Personalized Distributed Learning with Data and Node Heterogeneity

IEEE Transactions on Cognitive communications and networking 2025年

作者： Tian, Zhuojun Zhang, Zhaoyang Li, Yiwei Bennis, Mehdi Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China University of Oulu Center for Wireless Communications Oulu90014 Finland State Key Laboratory of Industrial Control Technology Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multimodal Communication Networks and Intelligent Information Processing Hangzhou310027 China Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China

To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis (DSLTH), based on which a communication-efficient personalized learning algorithm is developed. In the proposed method, each local model is represented as the ‌Hadamard product of global real-valued parameters and a personalized binary mask for pruning. The local model is learned by updating and fusing the personalized binary masks while the real-valued parameters are fixed among different agents. To further reduce the complexity of hardware implementation, we incorporate a group sparse regularization term in the loss function, enabling the learned local model to achieve structured sparsity. Then, a binary mask aggregation algorithm is designed by introducing an intermediate aggregation tensor and adding a personalized fine-tuning step in each iteration, which constrains model updates towards the local data distribution. The proposed method effectively leverages the relativity among agents while meeting personalized requirements in heterogeneous node conditions. We also provide a theoretical proof for the DSLTH, establishing it as the foundation of the proposed method. Numerical simulations confirm the validity of the DSLTH and demonstrate the effectiveness of the proposed algorithm. © 2015 IEEE.

关键词： Iterative methods

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Propagation properties and spatial-mode UWOC performance of quasi-perfect optical vortex beam in an improved oceanic channel

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Optics and Laser Technology 2025年 188卷

作者： Xiao, Zhiwei Zhou, Jian Wang, Lin Liu, Guizhen Ding, Zhongjun State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan430070 China School of Information Engineering Wuhan University of Technology Wuhan430070 China Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks Wuhan University of Technology Wuhan430070 China National Deep Sea Center Qingdao266237 China

In this study, the Quasi-perfect optical vortex (Quasi-POV) beam with topological charge-independence radial distribution is investigated to enhance the performance of underwater wireless optical communication (UWOC) system based on spatial modes. Additionally, the oceanic channel model is modified to obtain more reliable simulation results. The propagation and communication performance of perfect optical vortex (POV) beam and Quasi-POV beam are compared and analyzed through the modified model. With the optimization of beam's parameters, Quasi-POV beam achieves lower bit-error rate (BER) and higher average capacity in multiple phase shift keying (M−PSK) modulated UWOC system. The results indicate that Quasi-POV beam receives higher normalized intensity and lower crosstalk probability than the POV beam, the average simulation results for the three topologic charge cases show that the BER of Quasi-POV beam at 100 m reduced by approximately 52%, the average capacity of Quasi-POV beam increased by approximately 13.3%. The Quasi-POV beam has better performance than the POV beam in Spatial-Mode UWOC system according to the simulation results, which is more suitable for UWOC system based on spatial modes with smaller values of topologic charge. © 2025 Elsevier Ltd

关键词： Vortex flow

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Energy-Efficient Interference Cancellation for Coordinated Multi-Point ISAC Systems

IEEE Transactions on Green Communications and Networking

引用

IEEE Transactions on Green communications and networking 2025年

作者： Niu, Yangyang Wei, Zhiqing Song, Zhiqun Feng, Zhiyong Wu, Huici Ma, Dingyou Liu, Haotian Zhang, Jinbo Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communications Ministry of Education Beijing100876 China National Key Laboratory of Advanced Communication Networks Hebei Shijiazhuang China Beijing University of Posts and Telecommunications National Engineering Lab for Mobile Network Technologies Beijing100876 China Pengcheng Laboratory Department of Broadband Communiation Shenzhen518006 China

Integrated sensing and communication (ISAC) systems leverage coordinated multi-point (CoMP) base stations (BSs) to deliver high-accuracy sensing and robust connectivity. However, the integration of sensing and communication in CoMP-ISAC systems faces significant challenges from interference within and among BSs, which adversely affects performance and increases energy consumption, thereby limiting commercial adoption. This paper proposes a CoMP-ISAC system design aimed at enabling energy-efficient interference cancellation through the collaborative optimization of BS mode selection and transceiver design among distributed BSs, while satisfying constraints related to communication quality of service (QoS), sensing output signal-to-clutter-plus-noise ratio (SCNR), and total transmit power budget. The BS mode selection involves identifying the sensing receiver by selecting the BS that maximally contributes to the SCNR and establishing associations between BSs and user equipment (UE). A branch-and-bound (B&B) algorithm is employed to address the mixed Boolean nonlinear problem associated with BS-UE associations, specifically focusing on the mitigation of multi-user interference at each branching step. Further, transmit beamforming and receive filters are alternately optimized using the zero-forcing (ZF) method to enhance interference suppression. To ensure convexity in the multi-scale fractional objective function, the dual quadratic transform (QT) is applied. Simulation results validate the effectiveness of the proposed algorithm. © 2017 IEEE.

关键词： Budget control

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Differentially Private Federated Stochastic Primal-Dual Learning for Internet of Vehicles

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IEEE Internet of Things Journal 2025年

作者： Li, Yiwei Wang, Shuai Chang, Tsung-Hui Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China The Chinese University of Hong Kong Shenzhen School of Science and Engineering Shenzhen Research Institute of Big Data Shenzhen518172 China

Federated learning (FL) has the potential to empower Internet-of-Vehicles (IoV) networks by enabling smart vehicles (SVs) to participate in the learning process under the orchestration of a vehicular service provider while keeping data locally. In this paper, we propose a novel federated stochastic primal-dual algorithm with differential privacy (FedSPD-DP) to ensure robust privacy protection for FL based IoV (FL-IoV) systems. The FedSPD-DP algorithm leverages multiple steps of local stochastic gradient descent (SGD) and partial client participation (PCP) to improve communication efficiency while incorporating differential privacy (DP) to ensure privacy protection. Our theoretical analysis explores the impact of these strategies on learning performance. Specifically, we demonstrate that the data sampling strategy and PCP enhance data privacy, while a larger number of local SGD steps may increase privacy leakage, revealing a non-trivial tradeoff between communication efficiency and privacy protection. Extensive experiments on real-world data validate the effectiveness of the proposed algorithm, showing superior performance compared to state-of-the-art FL algorithms, and confirming the analytical results and properties. © 2014 IEEE.

关键词： Federated learning

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On Least Squares Weighted Recursive Estimation of Clock Skew and Offset in wireless sensor networks

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Chinese Journal of Electronics 2017年第5期26卷 1041-1047页

作者： HU Bing SUN Zhixin Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing University of Posts and Telecommunications

Three clock synchronization algorithms for wireless sensor networks(WSNs) in Pairwise broadcast synchronization(PBS) mechanism are *** include the joint Least squares estimator(LS),joint Least squares weighted estimator(LSW) and joint Least squares weighted Recursive estimator(R-LSW).For these estimators,the corresponding algorithms are derived and described by assuming a Gaussian random delay *** PBS,these estimators can achieve the Cramer-Rao lower bound(CRLB) for both listening node and active node without knowledge of the deterministic *** purpose of considering R-LSW is to reduce the use of storage space with the method of estimating while *** and analytical results verify that the estimators are efficient.

关键词： Clock synchronization wireless sensor networks(WSNs) Pairwise broadcast synchronization(PBS) Least squares estimator(LS)

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LANDMARC Localization Algorithm Based on Weight Optimization

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Chinese Journal of Electronics 2018年第6期27卷 1291-1296页

作者： HU Bing PENG Huijun SUN Zhixin Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing University of Posts and Telecommunications

In order to solve the problem that the difference of Received signal strength(RSS) between tags will become large when tags are close to the reader, which exists in LANDMARC system, a LANDMARC localization algorithm based on weight optimization is proposed in the paper. We optimize the weight by redefining the formulas of in-weight and ex-weight. In-weight formula is discussed under the free space propagation model. The definition of ex-weight is obtained by analyzing the relationship between RSS and distance under the log-distance path loss model. We evaluate the performance of the proposed algorithm and compare it with the algorithm based on normalized weight. The simulation results show the superior performance of the proposed algorithm in terms of location accuracy.

关键词： Location identification based on dynamic active RFID calibration(LANDMARC) system Radio frequency identification(RFID) Indoor localization Weight optimization

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Energy- and Latency-Efficient Resource Allocation for RIS-Assisted UAV-USV Cooperative MEC network

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green communications and networking 2025年

作者： Liao, Yangzhe Liu, Lin Ma, Yong Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks Wuhan University of Technology Wuhan430070 China School of Information Engineering Wuhan University of Technology Wuhan430070 China State Key Laboratory of Maritime Technology and Safety School of Navigation Hubei Key Laboratory of Inland Shipping Technology Wuhan University of Technology Wuhan430063 China Sanya Science and Education Innovation Park Wuhan University of Technology Sanya572000 China

The potential of cooperative unmanned aerial vehicle (UAV)-unmanned surface vehicle (USV) multi-access edge computing (MEC) platform cannot be fully revealed without thoroughly investigating USVs bidirectional data computation. In this paper, a novel reconfigurable intelligent surface (RIS)-assisted UAV-USV cooperative MEC network architecture is proposed considering USVs bidirectional tasks with hard time window. The weighted sum minimization of UAVs energy consumption and task execution latency is formulated by jointly considering USVs task execution mode selection indicators, UAVs flight route indicators, UAVs arrival time, UAVs hovering coordinates and RIS phase shift vector. A heuristic solution is proposed to solve the formulated challenging problem, where we divide the original problem into three subproblems, i.e., UAVs flight route indicators subproblem, the joint task execution mode selection indicators and UAVs arrival time subproblem and the joint UAVs hovering coordinates and RIS phase shift vector design subproblem;each of which is solved by the proposed enhanced grey wolf optimizer (EGWO) algorithm, the integer constrained-removed augmented Lagrangian (ICRAL) algorithm and the proposed multi-objective differential evolution (MODE) algorithm, respectively. The results verify that the proposed solution can significantly decrease the weighted sum of UAVs energy consumption and task execution latency in comparison with numerous selected advanced algorithms. © 2025 IEEE.

关键词： Resource allocation

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Improved finite-size analysis for measurement-device-independent quantum digital signature

arXiv

引用

arXiv 2025年

作者： Zhu, Jia-Li Zhang, Chun-Hui Wang, Yue-Ying Wang, Qin Institute of quantum information and technology Nanjing University of Posts and Telecommunications Nanjing210003 China "Broadband Wireless Communication and Sensor Network Technology" Key Lab of Ministry of Education NUPT Nanjing210003 China "Telecommunication and Networks" National Engineering Research Center NUPT Nanjing210003 China

Quantum digital signatures (QDS), based on the principles of quantum mechanics, provide information-theoretic security, ensuring the integrity, authenticity, and non-repudiation of data transmission. With present QDS protocols, measurement-device-independent QDS (MDI-QDS) can resist all attacks on detections, yet it suffers from finite-size effect. In this work, we present and compare three parameter estimation models for finite-size analysis of two-decoy MDI-QDS. The first model is a commonly used model in previous schemes, and we propose two new models to improve the performance. Subsequently, we perform numerical simulations to evaluate the performance of the three models. The results demonstrate that the proposed methods are less affected by finite-size effect, thereby effectively enhancing the signature rate. This work contributes to the practical development of QDS. Copyright © 2025, The Authors. All rights reserved.

关键词： Authentication

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Hybrid Implementation for Untrusted-node-based Quantum key Distribution network

arXiv

引用

arXiv 2025年

作者： Liu, Jingyang Zhou, Xingyu Ding, Huajian Xu, Jiaxin Zhang, Chunhui Li, Jian Wang, Qin Institute of quantum information and technology Nanjing University of Posts and Telecommunications Nanjing210003 China "Broadband Wireless Communication and Sensor Network Technology"Key Lab of Ministry of Education Ministry of Education Nanjing210003 China "Telecommunication and Networks"National Engineering Research Center NUPT Nanjing210003 China

Quantum key distribution (QKD) serves as a cornerstone of secure quantum communication, providing unconditional security grounded in quantum mechanics. While trusted-node networks have facilitated early QKD deployment, their vulnerability to node compromise underscores the need for untrusted-node architectures. Measurement-device-independent QKD (MDI-QKD) and twin-field QKD (TF-QKD) have emerged as leading candidates, addressing security vulnerabilities and extending transmission distances. Despite the wide adoptions in various fiber scaling, no integrated implementation of these two protocols has been demonstrated to date. Here, we present a hybrid system that seamlessly integrates TF-QKD and MDI-QKD into one untrusted-node-based architecture. Utilizing an efficient phase estimation method based on asymmetric interferometers, we convert twin-field global phase tracking to relative phase calibration, allowing near continuous running of both protocols. Experiments demonstrate secure finite-size key rates for sending-or-not-sending QKD and MDI-QKD over fiber distances of 150 to 431 km. The results align with theoretical simulations and show the ability to surpass the absolute repeaterless key capacity. Our work offers an unified framework for deploying multi-protocol QKD networks, laying the foundation for adaptable and scalable quantum infrastructures that can meet a wide range of security and performance needs. Copyright © 2025, The Authors. All rights reserved.

关键词： Quantum communication

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Simplification of I-Vector Extraction for Speaker Identification

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Chinese Journal of Electronics 2016年第6期25卷 1121-1126页

作者： XU Longting YANG Zhen SUN Linhui Broadband Wireless Communication and Sensor Network Technology Key Lab Nanjing University of Posts and Telecommunications

The identity vector(i-vector) approach has been the state-of-the-art for text-independent speaker recognition, both identification and verification in recent years. An i-vector is a low-dimensional vector in the socalled total variability space represented with a thin and tall rectangular matrix. This paper introduces a novel algorithm to improve the computational and memory requirements for the application. In our method, the series of symmetric matrices can be represented by diagonal expression,sharing the same dictionary, which to some extent is analogous to eigen decomposition, and we name this algorithm Eigen decomposition like factorization(EDLF). Similar algorithms are listed for comparison, in the same condition,our method shows no disadvantages in identification accuracy.

关键词： Speaker identification Closed-set I-vector Symmetric matrix factorization

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