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Sensing-communication-Computation Integration for Federated Edge Learning with Controllable Model Dropout

IEEE Internet of Things Journal 2025年

作者： Jiao, Xiang Zhu, Guangxu Jiang, Wei Chen, Li Luo, Wu Wen, Dingzhu State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Shenzhen Research Institute of Big Data Shenzhen China The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China The CAS Key Laboratory of Wireless Optical Communication University of Science and Technology of China Hefei China Network Intelligence Center School of Information Science and Technology ShanghaiTech University Shanghai China

FEderated Edge Learning (FEEL) is an advanced paradigm in edge artificial intelligence, enabling privacy-preserving collaborative model training through periodic communication between edge devices and a central server. FEEL involves three key processes: sensing, computation, and communication for data acquisition, processing, and exchange, respectively. Due to limited system resources, optimizing each process individually may lead to suboptimal learning performance. This challenge has sparked research into Integrated Sensing-Computation-communication (ISCC) design for enhanced FEEL. While previous work has optimized general learning parameters such as batch size and computing frequency, there is a lack of customized designs considering the neural network architecture as an optimizable variable in ISCC for FEEL. To close this gap, we introduce a novel design where each device generates a sub-model through controllable weight dropout, adding flexibility by directly manipulating the learning process and reducing computation and communication overhead. To guide ISCC resource allocation in this new setting, we present a comprehensive convergence analysis, revealing the tight coupling of sensing, computation, and communication across devices and their impact on FEEL convergence. Building on these theoretical insights, we formulate an ISCC problem aiming to maximize the FEEL convergence rate through joint optimization of variables such as batch size, sensing power, dropout rate, and communication power. This non-convex problem is decomposed into two sub-problems via alternating optimization: one controls batch size using a sorting algorithm, while the other focuses on ISCC device parameters, transformable into a convex problem solved by successive convex approximation. Extensive experiments using human motion recognition datasets demonstrate the superiority of the proposed design over baseline schemes. © 2014 IEEE.

关键词： Federated learning

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Arbitrary Waveform Frequency Modulated Continuous Wave LiDAR System

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Pang, Anning Yan, Zhongji Zhang, Tianzhu Hai, Yalong Dang, Anhong Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China

With advantages of high-precision 3-D imaging and simultaneous measurement of target distance and velocity, frequency-modulated continuous-wave (FMCW) light detection and ranging (LiDAR) has great potential in the fields of autonomous driving, military, and aerospace. However, frequency-modulated (FM) nonlinearity significantly deteriorates its ranging accuracy and has become a problem that cannot be neglected. This article proposes an arbitrary waveform FMCW (AW-FMCW) system, in which the distance of target is extracted precisely irrespective of the FM waveform employed. In proposed AW-FMCW system, the correlation between the phase of coherent signal and the FM waveform of tunable laser is rigorously deduced and analyzed. The distance of target is extracted utilizing minimum mean-square-error (MMSE) estimation. The low-bandwidth short-distance (LBSD) approximation is proposed to simplify the process of the estimation and quadrature coherent detection is employed to acquire the phase signal. The performance in terms of the measured distance and the precision of AW-FMCW system is theorized in detail and validated by Monte Carlo simulations and experiments. In the experiments, three different FM waveforms are utilized for ranging of targets at six different distances, and 0.279 mm ranging precision and 1.35× 10-4 relative precision are realized at 2.06 m target detection. © 1963-2012 IEEE.

关键词： Frequency shift keying

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Smoothed analysis-based noise manipulation for spatial photonic Ising machines

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Chinese Optics Letters 2025年第03期 114-119页

作者：叶新张文甲何祖源 State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University

The photonic Ising machine,a promising non-von Neumann computational paradigm,offers a feasible way to address combinatorial optimization *** develop a digital noise injection method for spatial photonic Ising machines based on smoothed analysis,where noise level acts as a parameter that quantifies the smoothness *** experiments with 20736-node Max-Cut problems,we establish a stable performance within a smoothness degree of 0.04 to *** noise injection results in a 24% performance enhancement,showing a 73% improvement over heuristic Sahni-Gonzales (SG) ***,to address noise-induced instability concerns,we propose an optoelectronic co-optimization method for a more streamlined smoothing method with strong stability.

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All-optical Inhibitory Dynamics by Backscattering With Unidirectional Injection-Locked Photonic Spiking Neuron

IEEE Photonics Journal

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IEEE Photonics Journal 2025年第3期17卷

作者： Zhou, Shengyao Ma, Bowen Zou, Weiwen Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center Department of Electronic Engineering Shanghai200240 China

Inhibitory dynamics plays an important role in the information processing of biological spiking neurons, where incoming stimuli weaken the activity level of neurons. Due to the lack of prohibitive physical effects in photonics, the realization of the photonic spiking neuron (PSN) with intrinsic inhibitory dynamics and the application of efficient inhibitory dynamics in the optical domain have been challenging. Herein, we propose a PSN with all-optical inhibitory dynamics, which is achieved by intrinsic backscattering from the unidirectional-emitted semi-conductor ring laser (SRL) to the master laser. The photonic spiking dynamics of the SRL operating in unidirectional mode were investigated, demonstrating the computational properties of the PSN as a leaky integrate-and-fire neuron. We prove that as the backscattering intensity increases, the number of spikes generated under the same input signal decreases. Under the influence of backscattering, the number of spikes fired increases with the input signal rate. In the speech signal classification task, the classification accuracy improves from 89% to 94% under the influence of inhibitory dynamics. This suggests that the presence of inhibitory dynamics helps filter out unwanted interference information. The results show the potential of backscattering-based inhibition dynamics for facilitating advanced neuromorphic information processing. © 2009-2012 IEEE.

关键词： Backscattering

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Synesthesia of Machines Based Multi-Modal Intelligent V2V Channel Model

arXiv

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arXiv 2025年

作者： Han, Zengrui Bai, Lu Huang, Ziwei Cheng, Xiang State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Shandong University Jinan250101 China

This paper proposes a novel sixth-generation (6G) multi-modal intelligent vehicle-to-vehicle (V2V) channel model from light detection and ranging (LiDAR) point clouds based on Synesthesia of Machines (SoM). To explore the mapping relationship between physical environment and electromagnetic space, a new V2V high-fidelity mixed sensing-communication integration simulation dataset with different vehicular traffic densities (VTDs) is constructed. Based on the constructed dataset, a novel scatterer recognition (ScaR) algorithm utilizing neural network SegNet is developed to recognize scatterer spatial attributes from LiDAR point clouds via SoM. In the developed ScaR algorithm, the mapping relationship between LiDAR point clouds and scatterers is explored, where the distribution of scatterers is obtained in the form of grid maps. Furthermore, scatterers are distinguished into dynamic and static scatterers based on LiDAR point cloud features, where parameters, e.g., distance, angle, and number, related to scatterers are determined. Through ScaR, dynamic and static scatterers change with the variation of LiDAR point clouds over time, which precisely models channel non-stationarity and consistency under different VTDs. Some important channel statistical properties, such as time-frequency correlation function (TF-CF) and Doppler power spectral density (DPSD), are obtained. Simulation results match well with ray-tracing (RT)-based results, thus demonstrating the necessity of exploring the mapping relationship and the utility of the proposed model. Copyright © 2025, The Authors. All rights reserved.

关键词： Vehicle-to-grid

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Secure encryption system based on quantum access network 4

Secure encryption system based on quantum access network

引用

4th International Computational Imaging Conference, CITA 2024

作者： Liu, Yuchao Wang, Tao Xu, Yuehan Zeng, Guihua State Key Laboratory of Advanced Optical Communication Systems and Networks Center of Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai200240 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Hefei National Laboratory CAS Center for Excellence in Quantum Information and Quantum Physics Hefei230026 China

ISBN: (纸本)9781510688834

Quantum secure communication technology, grounded in the principles of quantum mechanics, has revolutionized traditional cryptographic methods, which predominantly rely on mathematical algorithms and logical transformations. Quantum key distribution (QKD) facilitates the secure sharing of symmetric keys between legitimate parties, ensuring the integrity and confidentiality of information in communication channels. Among various QKD schemes, continuous variable quantum key distribution (CV-QKD) has emerged as a viable alternative to the more established discrete variable quantum key distribution (DV-QKD). CV-QKD boasts several advantages, including straightforward deployment, reduced operational costs, and stable signal quality, positioning it as a significant component of the quantum communication *** noise stream cipher (QNSC) represents a technique that employs redundant data streams to encrypt plaintext. Notably, QNSC shares structural similarities with the optical path used in quantum key distribution, allowing for compatibility with existing QKD infrastructure. Furthermore, the keys generated through quantum key distribution ensure absolute security, enabling them to substitute the data streams produced by pseudo-random sequences traditionally used in classical encryption schemes. This substitution enhances the overall security framework of the quantum noise stream encryption *** quantum access network (QAN) extends quantum key distribution capabilities from point-to-point connections to point-to-multipoint configurations, thereby becoming an essential component of contemporary network architectures. By interlinking multiple end users with a network backbone, quantum access networks can seamlessly integrate with quantum key distribution protocols. This integration offers a cost-effective and scalable solution for user access to the *** experimental verifications have demonstrated the viability of downstream access networks,

关键词： Quantum noise

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Security analysis of mode-pairing quantum key distribution with flexible pairing strategy

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Optics Express 2025年第11期33卷 23939-23959页

作者： Yi-Fei Lu Yang Wang Yan-Yang Zhou Yu Zhou Xiao-Lei Jiang Xin-Hang Li Hai-Tao Wang Jia-Ji Li Chun Zhou Hong-Wei Li Yu-Yao Guo Lin-Jie Zhou Wan-Su Bao Henan Key Laboratory of Quantum Information and Cryptography IEU Zhengzhou 450001 China wy@*** State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Department of Electronic Engineering Shanghai Jiao Tong University Shanghai 200240 China bws@***

Mode-pairing quantum key distribution (MP-QKD) is advantageous for long-distance secure communication, leveraging its simple implementation and quadratic scaling capacity. The post-measurement pairing in MP-QKD alleviates the photon-coincidence demands, which are essential for surpassing the fundamental limit to the key-rate transmission. In this work, we propose an improved decoy-state MP-QKD protocol featuring a flexible and efficient pairing strategy. We prove the security of the proposed scheme by presenting an entanglement model for decoy-state MP-QKD. The simulation results show that the secret key rate (SKR) can be enhanced among all distances. Notably, compared with the original scheme [Nature communication 13 , 3903 (2022) [ CrossRef ] ], the improvement of SKR is greater than 65% within 375 km in the asymptotic case and greater than 50% within 400 km in the finite case. And the achievable distance can be extended in the finite case, especially with a small block length. The simulation results demonstrate the high efficiency of the proposed scheme, which is expected to promote the practical applicability of MP-QKD. Furthermore, the entanglement model could provide a theoretical framework for further security and performance analysis of decoy-state MP-QKD.

关键词： Integrated photonics Phase compensation Phase estimation Quantum communications Quantum key distribution Variable optical attenuators

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Directivity-Aware Degrees of Freedom Analysis for Extremely Large-Scale MIMO

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IEEE Transactions on Vehicular Technology 2025年

作者： Yue, Shaohua Liu, Liang Di, Boya The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China The Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong

Extremely large-scale multiple-input multiple-output (XL-MIMO) communications, enabled by numerous antenna elements integrated into large antenna surfaces, can provide increased effective degree of freedom (EDoF) to achieve high diversity gain. However, it remains an open problem that how the EDoF is influenced by the directional radiation pattern of antenna elements. In this work, empowered by the wavenumber-domain channel representation, we analyze the EDoF in a general case where the directivity of antennas, determined by the antenna structure and element spacing, is considered. Specifically, we first reveal the uneven distribution of directivity-aware wavenumber-domain coupling coefficients, i.e., channel gain towards different directions, in the isotropic Rayleigh fading channel. EDoF is then calculated based on such distribution of coupling coefficients. A numerical method is also provided to obtain coupling coefficients via full-wave EM simulations. Due to the influence of antenna directivity, how EDoF and ergodic channel capacity vary with the element spacing are explored via simulations for different antenna types. © 1967-2012 IEEE.

关键词： Degrees of freedom (mechanics)

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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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Brillouin random lasing resonance enabled fast light and superluminal propagation in optical fibers

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Optics Express 2025年第11期33卷 22497-22510页

作者： Haoran Xie Zhelan Xiao Zhiming Liu Liwen Sheng Li Zhan Fufei Pang Liang Zhang Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai 200444 China Ceyear Technologies Co. Ltd. Qingdao 266555 China Shandong Electronic Test & Measurement Technology Innovation Center Qingdao 266555 China liuzhimingsky@*** State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China liangzhang@***

We proposed and demonstrated fast light and superluminal propagation based on Rayleigh scattering-induced Brillouin random lasing resonance in optical fibers. A theoretical model of the proposed Brillouin superluminal propagation system has been established, detailing the principle of optical group velocity manipulation based on the combination of stimulated Brillouin scattering and Brillouin cross-gain modulation, for the first time to the best of our knowledge. Thanks to the randomly distributed Rayleigh scattering, Brillouin random lasing resonance with a single-longitudinal-mode lasing operation essentially contributes to fast light and superluminal propagation of the pump light signals propagating along a kilometer-long optical fiber. The temporal advancement, group velocity, and group index of sinusoidally modulated pump signals are thoroughly compared in experiments, which agree well with simulations. The dependence of the Brillouin gain fibers on the group velocity as well as the impact of Stokes power under different signal modulation frequencies on the broadening factor are systematically discussed and characterized. Furthermore, the Brillouin random lasing fast-light system is developed to offer a unique time-domain analysis solution for high-sensitivity fiber Bragg grating (FBG) temperature sensing scheme. Scalable sensitivity of the proposed sensing system can be achieved by applying different modulation frequencies. These findings may find wide potential applications in optical signal processing and hyper-sensitive detection.

关键词： Brillouin scattering Frequency modulation Nonlinear optical fibers optical signals Raman scattering Signal processing

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