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International Conference on communication technology (ICCT)

作者： Jiang Bin Lu An'nan You Mingyi Lou Caiyi Ye Yunxia Huang Kai Shi Binhua Communication Information Security Control Laboratory No.36 Research Institute of CETC Jiaxing Jiaxing China

Passive location system that locates “silent” targets using an non-cooperative opportunistic source (also called external illuminator) is great importance in a variety of applications. To solve the problem of using a single observation station to receive a single external radiation source signal to realize the target location, the paper proposes a weighted least squares location algorithm combining direction finding and time difference information. In this algorithm, the location problem is constructed as a weighted least squares model considering the error of each measurement information, and then the grid search strategy is used to solve the model to obtain the target location. After that, the positioning error of the algorithm is theoretically analyzed, and the influence of direction finding error, measurement time difference error, observation station position error and external radiation source position error on the target positioning error is studied. Finally, the performance of the algorithm is verified by several simulation tests.

关键词： Location awareness Weight measurement Simulation Measurement uncertainty Position measurement Search problems Time measurement

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Defense of Signal Modulation Classification Attack Based on GAN 7th

Defense of Signal Modulation Classification Attack Based on ...

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7th China National Conference on Big Data and Social Computing, BDSC 2022

作者： Zhu, Jiawei Liu, Yuhang Xu, Dongwei Yang, Hao Xuan, Qi Wang, Shunling Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China

ISBN: (纸本)9789811975318

Although deep learning has been broadly used in all kinds of domains and has also achieved very good performance, it is obvious that deep learning is very vulnerable to be attacked shown by extensive researches (e.g. even a very small perturbation is added to the raw signal data, the result of the modulation classification of the signal by the deep neural network will be wrong), which will cause serious consequences. Thus, it is necessary to find some ways to defense this attack. As a new deep learning model in recent years, Generative Adversarial Network (GAN) has been applied to the field of radio communication, which can encrypt the signal data, so as to ensure the reliable transmission of the signal. In this paper, a defense method against signal modulation classification attack based on GAN is developed, which is used to utilize generator to reconstruct the signal sample to improve the classification accuracy of the model, while the defense ability of the model against adversarial samples is improved. It has been shown that the method achieved good results in experiments. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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A Collaborative Jamming Algorithm Based on Multi-UAV Scheduling 23

A Collaborative Jamming Algorithm Based on Multi-UAV Schedul...

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23rd IEEE International Conference on communication technology, ICCT 2023

作者： Jiang, Yixin Zhou, Lingyun Tang, Yijia Tu, Ya Liu, Chunhong Shi, Qingjiang Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China School of Software Engineering Tongji University Shanghai201804 China Shenzhen Research Institute of Big Data Shenzhen518172 China

ISBN: (纸本)9798350325959

In this paper, we consider the problem of multi-unmanned aerial vehicles' (UAVs), scheduling for cooperative jamming, where UAVs equipped with directional antennas perform collaborative jamming tasks against several targets of interest. To ensure effective jamming towards the targets, we formulate it as an non-convex optimization problem, aiming to minimize the communication performance of the targets by jointly optimizing UAVs' deployment and directional antenna orientations. Due to the unique structure of the problem, we derive an equivalent transformation by introducing a set of auxiliary matrices. Subsequently, we propose an efficient iterative algorithm based on the alternating direction method of multi-pliers (ADMM), which decomposes the problem into multiple tractable subproblems solved in closed-form or by gradient projection method. Extensive simulations validate the efficacy of the proposed algorithm. © 2023 IEEE.

关键词： ADMM improved Gradient Descend jamming system UAV deployment

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Weak Signal Detection based on Beta Divergence 24

Weak Signal Detection based on Beta Divergence

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24th IEEE International Workshop on Signal Processing Advances in Wireless communications, SPAWC 2023

作者： Liu, Jiahao Liu, Haoxuan Pu, Wenqiang Zhou, Rui You, Ming-Yi Shi, Qingjiang Science and Technology on Communication Information Security Control Laboratory Jiaxing China The Chinese University of HongKong Shenzhen Research Institute of Big Data Shenzhen China Tongji University School of Software Engineering Shanghai China

ISBN: (纸本)9781665496261

Among different electromagnetic spectrum monitoring tasks, a fundamental one is detecting the presence of weak communication signal under non-cooperative setting. Various detection methods have been studied in the literature. These detection methods usually construct a proper hypothesis testing metric to distinguish the signal-plus-noise and noise-only signals. information entropy based metric has recently been studied and shown its superiority over traditional energy based metrics. We find that it can be explained as a realization of the general Kullback-Leibler divergence. Inspired by that, in this paper, we propose to detect the signal using a statistic divergence called β-divergence. Different choices of β will lead to several well known divergences, e.g., Itakura-Saito divergence and Euclidean distance. We study its detection performance for non-cooperative signal sources. Both simulation and real experiments demonstrate that β-divergence can improve detection performance for various modulation types of communication signals. © 2023 IEEE.

关键词： Cooperative communication

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An Optimal Beamforming Model for Aperture-Level Phased Array Full-Duplex 13

An Optimal Beamforming Model for Aperture-Level Phased Array...

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13th International Conference on Microwave and Millimeter Wave technology, ICMMT 2021

作者： Chen, Jiarui Chen, Shunyang Huang, Xiaoguo Zhang, Qi Zhu, Menglei Science And Technology On Communication Information Security Control Laboratory Jiaxing314033 China

ISBN: (纸本)9781665434379

Full-duplex, which aims to simultaneously transmitting and receiving over the same band, together with phased array antennas play fundamental roles in next-generation wireless communication systems. The combination of them, phased array fullduplex, is widely accepted as a promising way for realizing practical full-duplex communications. However, diversified application scenarios and rapidly grown system complexity hinder the development of PAFD. In this work, we present a spatial domain selfinterference suppression method for the implementation of fullduplex in digital phased array architectures. By taking advantage of the flexibility of fully-digital phased array, a novel computation framework is constructed to effectively optimize the transmitting beamforming weights in order to maximize the desired beamforming gains of the transmitting sub-array while simultaneously reducing the self-interference received by receiving sub-array. Our work demonstrates the capability of spatial domain methods in digital phased array and paves the way for practical full-duplex communications. © 2021 IEEE.

关键词： Beamforming

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Modulation technology in Cross-Domain Magnetic Induction communication

Modulation Technology in Cross-Domain Magnetic Induction Com...

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IEEE International Conference on Signal Processing, communications and Computing (ICSPCC)

作者： Ruoxue Cheng Xin Zhang Xiaoming Qi Xiaoji Zhang Yizhou Ge School of Marine Science and Technology Northwestern Polytechnical University Xi'an China Control Laboratory Science and Technology on Communication Information Security Jiangxi China

ISBN: (数字)9798350366556

ISBN: (纸本)9798350366563

The research on technology of cross-domain communication, which spans air and sea domains, has been widely concerned. As an emerging cross-domain communication technology, magnetic induction (MI) communication boasts unique advantages such as stable channels, minimal susceptibility to the dynamic ocean environment, and low propagation delay. However, it also has limitations in terms of transmission distance×data rate. In this paper, the modulation technology in cross-domain magnetic induction communication is studied, and the very minimum shift keying (VMSK/2) coding modulation scheme based on direct sequence spread spectrum (DSSS) technology is proposed. VMSK modulation is used to adapt to the severely bandwidth-limited underwater magnetic induction channel, and DSSS technology is used to enhance the detection ability of weak magnetic induction signal, thereby increasing the water entry depth of cross-domain communication. In this paper, the scheme of VMSK/2-DSSS code modulation is given, and the simulation analysis and field trial are carried out. The simulation and lake test results show that compared to magnetic induction communication without DSSS, the VMSK/2-DSSS coding modulation scheme can achieve a greater water entry depth, enabling error-free cross-domain magnetic induction communication at a depth of 40 meters and a data rate of 100bps.

关键词： Underwater communication Bit error rate Modulation Magnetic domains Spread spectrum communication Lakes Encoding Signal detection Magnetic susceptibility Signal to noise ratio

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Analysis of Frequency Offset for Satellite Navigation Receiver Using Carrier-Aided Code Tracking Loop 20

Analysis of Frequency Offset for Satellite Navigation Receiv...

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20th IEEE International Conference on communication technology, ICCT 2020

作者： Gao, Teng Wang, Lijun Jin, Xiaofan No.36 Research Institute of Cetc Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781728181417

Carrier-aided code tracking loop is widely used in satellite navigation receivers. This kind of loop structure can reduce code tracking noise by narrowing the bandwidth of code tracking loop. The performance of carrier-aided code tracking loop in receivers is affected by frequency deviation of reference clock source. This paper analyzes the influence of carrier frequency offset and sampling frequency offset on carrier-aided code tracking loop due to reference clock offset. The results show that large frequency offset can cause code tracking loop lose lock, code tracking loop is more sensitive to sampling frequency deviation and increasing the loop bandwidth can reduce the effects of frequency offset. This analysis provides reference for receiver tracking loop design. © 2020 IEEE.

关键词： Bandwidth

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Cross-receiver specific emitter identification based on deep adversarial neural network with separated batch normalization 3

Cross-receiver specific emitter identification based on deep...

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3rd International Conference on Computer science and communication technology, ICCSCT 2022

作者： Huang, Keju Jiang, Bin Yang, Junan Wang, Jian Hu, Pengjiang Li, Yiming Shao, Kun Zhao, Dongxing College of Electronic Engineering National University of Defense Technology Hunan Changsha China Science and Technology on Communication Information Security Control Laboratory Zhejiang Jiaxing314000 China

ISBN: (纸本)9781510661240

Specific emitter identification (SEI) is the approach to identify emitter individuals using received wireless signals. Despite the fact that deep learning has been successfully applied in SEI, the performance is still unsatisfying when the receiver changes. In this paper, we introduce a domain adaptation method, namely deep adversarial neural network (DANN), for cross-receiver SEI. Furthermore, separated batch normalization (SepBN) is proposed to improve the performance. Results of experiments using real data show that the proposed SepBN-DANN method performs desirably for cross-receiver SEI. © 2022 SPIE.

关键词： Seebeck effect

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Primary User Adversarial Attacks on Deep Learning-Based Spectrum Sensing and the Defense Method

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China communications 2021年第12期18卷 94-107页

作者： Shilian Zheng Linhui Ye Xuanye Wang Jinyin Chen Huaji Zhou Caiyi Lou Zhijin Zhao Xiaoniu Yang Science and Technology on Communication Information Security Control Laboratory Jiaxing314000China College of Information Engineering Zhejiang University of TechnologyHangzhou310012China Institute of Cyberspace Security Zhejiang University of TechnologyHangzhou310012China School of Communication Engineering Hangzhou Dianzi UniversityHangzhou310018China

The spectrum sensing model based on deep learning has achieved satisfying detection per-formence,but its robustness has not been *** this paper,we propose primary user adversarial attack(PUAA)to verify the robustness of the deep learning based spectrum sensing *** adds a care-fully manufactured perturbation to the benign primary user signal,which greatly reduces the probability of detection of the spectrum sensing *** design three PUAA methods in black box *** or-der to defend against PUAA,we propose a defense method based on autoencoder named *** apply the long short-term memory network and the convolutional neural network together to DeepFilter,so that it can extract the temporal and local features of the input signal at the same time to achieve effective *** experiments are conducted to eval-uate the attack effect of the designed PUAA method and the defense effect of *** show that the three PUAA methods designed can greatly reduce the probability of detection of the deep learning-based spectrum sensing *** addition,the experimen-tal results of the defense effect of DeepFilter show that DeepFilter can effectively defend against PUAA with-out affecting the detection performance of the model.

关键词： spectrum sensing cognitive radio deep learning adversarial attack autoencoder defense

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An Anti-jamming Intelligent Decision-Making Method for Multi-user communication Based on Deep Reinforcement Learning 22

An Anti-jamming Intelligent Decision-Making Method for Multi...

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22nd IEEE International Conference on communication technology, ICCT 2022

作者： Zhang, Lan Ma, Liang Tian, Feng Liang, Tianyi Science and Technology on Communication Information Security Control Laboratory Jiaxing314000 China The 36th Research Institution of China Electronics Technology Group Corporation Jiaxing341000 China Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)9781665470674

In order to effectively cope with the external malicious jamming from jammers and avoid mutual interference caused by competitive channels among users, an intelligent antijamming decision-making method based on deep reinforcement learning for multi-user communication is proposed in this paper. In multiple jamming modes, the base station perceives the current spectrum information of the multi-user and the jammer and makes it as the input of the deep reinforcement learning strategy neural network, then selects the joint action according to the dynamic greedy algorithm, which will help the users intelligently select the communication frequency band via the feedback from the base station. The simulation results show that the proposed method effectively overcome the communication jamming induced by external jammers and internal users. Moreover, the normalized throughput of each user in the proposed algorithm is much higher than the random frequency hopping and fixed ϵ deep reinforcement learning algorithm with faster convergence speed. © 2022 IEEE.

关键词： Reinforcement learning

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