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Mode-dependent dynamic gain of all-fiber FM-EDFA under various pump manipulation

Chinese Optics Letters 2024年第2期22卷 128-134页

作者：方翼鸿张心怡黄锡恒曾研许鸥李建平付松年秦玉文 Institute of Advanced Photonics technology School of Information EngineeringGuangdong University of TechnologyGuangzhou 510006China guangdong Provincial {1. laboratory of information Photonics technology Guangdong University of TechnologyGuangzhou 510006China key {1. of Photonic technology for Integrated Sensing and Communication Ministry of EducationGuangdong University of TechnologyGuangzhou 510006China

The dynamic gain of a few-mode erbium-doped fiber amplifier(FM-EDFA)is vital for the long-haul mode division multiplexing(MDM)***,we investigate the mode-dependent dynamic gain of an FM-EDFA under various manipulations of the pump ***,we numerically calculate the gain variation with respect to the input signal power,where a modedependent saturation input power occurs under different pump *** under the fixed intensity profile of the pump laser,the saturation input power of each spatial mode is ***,high-order mode pumping leads to a compression of the linear amplification region,even though it is beneficial for the mitigation of the differential modal gain(DMG)arising in all guided ***,we develop an all-fiber 3-mode EDFA,where the fundamental mode of the pump laser can be efficiently converted to the LP_(1.)mode using the all-fiber mode-selective coupler(MSC).In comparison with the traditional LP_(01.pumping scheme,the DMG at 1.50 nm can be mitigated from 1.61.dB to 0.97 dB under the LP_(1.)mode pumping,while both an average gain of 1..93 dB and a DMG of less than 1.dB can be achieved from 1.30 nm to 1.60 ***,the corresponding signal input saturation powers are reduced by 0.3 dB for the LP_(01.mode and 1.6 dB for the LP_(1.)mode,*** theoretical and experimental results indicate that a trade-off occurs between the DMG mitigation and the extension of the linear amplification range when the intensity profile of pump laser is manipulated.

关键词： few-mode erbium-doped fiber amplifier differential modal gain saturation input power

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Linear shallow neural network to accelerate transmitter dispersion eye closure quaternary(TDECQ) assessment

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Science China(information Sciences) 2024年第4期67卷 337-338页

作者： Junjiang XIANG Zejun CHEN Yijun CHENG Hailin YANG Xuancheng HUO Meng XIANG Gai ZHOU Yuwen QIN Songnian FU Institute of Advanced Photonics technology School of Information EngineeringGuangdong University of Technology School of Optical and Electronic information Huazhong University of Science and Technology key {1. of Photonic technology for Integrated Sensing and Communication Ministry of Education of ChinaGuangdong University of Technology guangdong Provincial {1. laboratory of information Photonics technology Guangdong University of Technology

To support the ever-emerging capacity requirement of datacenter interconnection(DCI) applications, transmitter dispersion eye closure quaternary(TDECQ) has been proposed by IEEE802.3 standard [1., which is specifically employed for the four-level pulse amplitude modulation(PAM-4) signals. However, the traditional scheme of TDECQ assessment needs several iterative operations,

关键词： IEEE Standards

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Lightweight Object Detection Networks for UAV Aerial Images Based on YOLO

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Chinese Journal of Electronics 2024年第4期33卷 997-1009页

作者： Yanshan LI Jiarong WANG Kunhua ZHANG Jiawei YI Miaomiao WEI Lirong ZHENG Weixin XIE ATR National key {1. of Defense technology Shenzhen University guangdong {1. laboratory of Intelligent information Processing Shenzhen University

Existing high-precision object detection algorithms for UAV(unmanned aerial vehicle) aerial images often have a large number of parameters and heavy weight, which makes it difficult to be applied to mobile *** propose three YOLO-based lightweight object detection networks for UAVs, named YOLO-L, YOLO-S, and YOLO-M, respectively. In YOLO-L, we adopt a deconvolution approach to explore suitable upsampling rules during training to improve the detection accuracy. The convolution-batch normalization-Si LU activation function(CBS)structure is replaced with Ghost CBS to reduce the number of parameters and weight, meanwhile Maxpool maximum pooling operation is proposed to replace the CBS structure to avoid generating parameters and weight. YOLO-S greatly reduces the weight of the network by directly introducing CSPGhost Neck residual structures, so that the parameters and weight are respectively decreased by about 1.% at the expense of 2.4% mAP. And YOLO-M adopts the CSPGhost Neck residual structure and deconvolution to reduce parameters by 5.6% and weight by 5.7%, while m AP only by 1.8%. The results show that the three lightweight detection networks proposed in this paper have good performance in UAV aerial image object detection task.

关键词： Training YOLO Deconvolution Accuracy Object detection Autonomous aerial vehicles Feature extraction

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Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

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Computers, Materials & Continua 2024年第4期79卷 1705-1726页

作者： Aodi Liu Na Wang Xuehui Du Dibin Shan Xiangyu Wu Wenjuan Wang He’nan Province key {1. of information security Information Engineering UniversityZhengzhou450000China

Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access controlmechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policymanagement efficiency and difficulty in accurately describing the access control policy. To overcome theseproblems, this paper proposes a big data access control mechanism based on a two-layer permission decisionstructure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes areintroduced in the ABAC model as business constraints between entities. The proposed mechanism implementsa two-layer permission decision structure composed of the inherent attributes of access control entities and thebusiness attributes, which constitute the general permission decision algorithm based on logical calculation andthe business permission decision algorithm based on a bi-directional long short-term memory (BiLSTM) neuralnetwork, respectively. The general permission decision algorithm is used to implement accurate policy decisions,while the business permission decision algorithm implements fuzzy decisions based on the business *** BiLSTM neural network is used to calculate the similarity of the business attributes to realize intelligent,adaptive, and efficient access control permission decisions. Through the two-layer permission decision structure,the complex and diverse big data access control management requirements can be satisfied by considering thesecurity and availability of resources. Experimental results show that the proposed mechanism is effective andreliable. In summary, it can efficiently support the secure sharing of big data resources.

关键词： Big data access control data security BiLSTM

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Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics

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Journal of Systems Engineering and Electronics 2024年第1期35卷 24-30页

作者： TIAN Jing ZHANG Wei School of information and Electronics Beijing Institute of TechnologyBeijing 100081China National key {1. of Electromagnetic Space security Chengdu 610036China

In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial *** the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation *** cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range *** principle is presented,and the validity is proven by simulation results.

关键词： adaptive radar beamforming training sample selection non-homogeneous detector electronic jamming jamming suppression

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Spatial Distribution Feature Extraction Network for Open Set Recognition of Electromagnetic Signal

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 279-296页

作者： Hui Zhang Huaji Zhou Li Wang Feng Zhou The Ministry key {1. of Electronic information Countermeasure and Simulation Xidian UniversityXi’an710071China Science and technology on Communication {1. security Control laboratory Jiaxing314033China

This paper proposes a novel open set recognition method,the Spatial Distribution Feature Extraction Network(SDFEN),to address the problem of electromagnetic signal recognition in an open *** spatial distribution feature extraction layer in SDFEN replaces convolutional output neural networks with the spatial distribution features that focus more on inter-sample information by incorporating class center *** designed hybrid loss function considers both intra-class distance and inter-class distance,thereby enhancing the similarity among samples of the same class and increasing the dissimilarity between samples of different classes during ***,this method allows unknown classes to occupy a larger space in the feature *** reduces the possibility of overlap with known class samples and makes the boundaries between known and unknown samples more ***,the feature comparator threshold can be used to reject unknown *** signal open set recognition,seven methods,including the proposed method,are applied to two kinds of electromagnetic signal data:modulation signal and real-world *** experimental results demonstrate that the proposed method outperforms the other six methods overall in a simulated open ***,compared to the state-of-the-art Openmax method,the novel method achieves up to 8.87%and 5.25%higher micro-F-measures,respectively.

关键词： Electromagnetic signal recognition deep learning feature extraction open set recognition

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FL-EASGD:Federated Learning Privacy security Method Based on Homomorphic Encryption

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Computers, Materials & Continua 2024年第5期79卷 2361-2373页

作者： Hao Sun Xiubo Chen Kaiguo Yuan information {1. Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China

Federated learning ensures data privacy and security by sharing models among multiple computing nodes instead of plaintext ***,there is still a potential risk of privacy leakage,for example,attackers can obtain the original data through model inference ***,safeguarding the privacy of model parameters becomes *** proposed solution involves incorporating homomorphic encryption algorithms into the federated learning ***,the existing federated learning privacy protection scheme based on homomorphic encryption will greatly reduce the efficiency and robustness when there are performance differences between parties or abnormal *** solve the above problems,this paper proposes a privacy protection scheme named Federated Learning-Elastic Averaging Stochastic Gradient Descent(FL-EASGD)based on a fully homomorphic encryption ***,this paper introduces the homomorphic encryption algorithm into the FL-EASGD scheme to preventmodel plaintext leakage and realize privacy security in the process ofmodel ***,this paper designs a robust model aggregation algorithm by adding time variables and constraint coefficients,which ensures the accuracy of model prediction while solving performance differences such as computation speed and node anomalies such as downtime of each *** addition,the scheme in this paper preserves the independent exploration of the local model by the nodes of each party,making the model more applicable to the local data ***,experimental analysis shows that when there are abnormalities in the participants,the efficiency and accuracy of the whole protocol are not significantly affected.

关键词： Federated learning homomorphic encryption privacy security stochastic gradient descent

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Constructing the Impossible Differential of Type-II GFN with Boolean Function and Its Application to WARP

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Chinese Journal of Electronics 2024年第1期33卷 80-89页

作者： Jiali SHI Guoqiang LIU Chao LI College of Liberal Arts and Sciences National University of Defense Technology Hunan Engineering Research Center of Commercial Cryptography Theory and technology Innovation State key {1. of information security Institute of Information Engineering

Type-Ⅱ generalized Feist el network(GFN) has attracted a lot of attention for its simplicity and high *** differential attack is one of the powerful cryptanalytic approaches for word-oriented block ciphers such as Feistel-like *** deduce the impossible differential of Type-Ⅱ GFN by analyzing the Boolean function in the middle *** main idea is to investigate the expression with the variable representing the plaintext(ciphertext) difference words for the internal state *** adopting the miss-in-the-middle approach,we can construct the impossible differential of Type-Ⅱ *** an illustration,we apply this approach to WARP,a lightweight 1.8-bit block cipher with a 1.8-bit key which was presented by Banik et *** SAC *** structure of WARP is a 32-branch Type-Ⅱ ***,we find two 21.round truncated impossible differentials and implement a 32-round key recovery attack on *** the 32-round key recovery attack on WARP,some observations are used to mount an effective *** the advantage of the early abort technique,the data,time,and memory complexities are 21.5.69chosen plaintexts,21.6.6832-round encryptions,and 21.0-bit,*** the best of our knowledge,this is the best attack on WARP in the single-key scenario.

关键词： Ciphers Boolean functions Parallel processing Complexity theory

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A new quantum key distribution resource allocation and routing optimization scheme

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Chinese Physics B 2024年第3期33卷 244-259页

作者：毕琳袁晓同吴炜杰林升熙 School of Computer Science and technology Changchun University of Science and TechnologyChangchun 130012China key {1. of Network and information security in Jilin Province Changchun 130012China

Quantum key distribution(QKD)is a {1. that can resist the threat of quantum computers to existing conventional cryptographic ***,due to the stringent requirements of the quantum key generation environment,the generated quantum keys are considered valuable,and the slow key generation rate conflicts with the high-speed data transmission in traditional optical *** this paper,for the QKD network with a trusted relay,which is mainly based on point-to-point quantum keys and has complex changes in network resources,we aim to allocate resources reasonably for data packet ***,we formulate a linear programming constraint model for the key resource allocation(KRA)problem based on the time-slot ***,we propose a new scheduling scheme based on the graded key security requirements(GKSR)and a new micro-log key storage algorithm for effective storage and management of key ***,we propose a key resource consumption(KRC)routing optimization algorithm to properly allocate time slots,routes,and key *** results show that the proposed scheme significantly improves the key distribution success rate and key resource utilization rate,among others.

关键词： quantum key distribution(QKD) resource allocation key storage routing algorithm

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Vision-Based Adaptive Prescribed-Time Control of UAV for Uncooperative Target Tracking with Performance Constraint

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Journal of Systems Science & Complexity 2024年第5期37卷 1956-1977页

作者： SHE Xuehua MA Hui REN Hongru LI Hongyi School of Automation and the guangdong Provincial {1. laboratory of Intelligent Decision and Cooperative Control Guangdong University of TechnologyGuangzhou 510006China School of Mathematics and Statistics Guangdong University of TechnologyGuangzhou 510006China College of Electronic and information Engineering and Chongqing {1. laboratory of Generic technology and System of Service Robots Southwest UniversityChongqing 400715China

This paper discusses the uncooperative target tracking control problem for the unmanned aerial vehicle(UAV)under the performance constraint and scaled relative velocity constraint,in which the states of the uncooperative target can only be estimated through a vision *** the limited detection range,a prescribed performance function is designed to ensure the transient and steady-state performances of the tracking ***,the scaled relative velocity constraint in the dynamic phase is taken into account,and a time-varying nonlinear transformation is used to solve the constraint problem,which not only overcomes the feasibility condition but also fails to violate the constraint ***,the practically prescribed-time stability technique is incorporated into the controller design procedure to guarantee that all signals within the closed-loop system are *** is proved that the UAV can follow the uncooperative target at the desired relative position within a prescribed time,thereby improving the applicability of the vision-based tracking *** results have been presented to prove the validity of the proposed control strategy.

关键词： Nonlinear transformation performance constraint prescribed-time tracking uncooperative target vision-based measurement

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