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IEEE International Symposium on Personal, Indoor and Mobile Radio communications (PIMRC)

作者： Hang Que Jie Yang Tao Du Shuqiang Xia Chao-Kai Wen Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China ZTE Corporation Shenzhen China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

The advancement of millimeter-wave communication technology heralds new sensing capabilities. By leveraging channel multipath parameter estimates, we can harness simultaneous localization and mapping (SLAM) for precise user equipment (UE) localization and radio map construction in 6 G communication systems. Particularly in multi-UE scenarios, SLAM empowers base stations to amalgamate the local radio maps of various UEs efficiently. This study introduces a novel Bayesian framework specifically designed for multi-UE SLAM, complemented by a tailored factor graph. We also unveil a two-stage multi-UE SLAM algorithm. Our simulation results reveal that this algorithm substantially enhances radio map construction accuracy by $\mathbf{4 8. 5 \%}$ and UE localization accuracy by $13.5 \%$, outperforming single-UE cases. Moreover, the algorithm demonstrates remarkable adaptability to environmental changes, showcasing its potential for long-term evolution in dynamic settings.

关键词： Location awareness Simultaneous localization and mapping Accuracy communication systems Heuristic algorithms Simulation Bayes methods Sensors Millimeter wave communication Land mobile radio

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A 3-D Printed Ka-Band Waveguide Bandpass Filter With Quasi-Elliptic Response

A 3-D Printed Ka-Band Waveguide Bandpass Filter With Quasi-E...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Fan Zhang Lili Xu Jianqiang Zhang Pulong Nan Xiaofan Jin Gaofeng Pan Science and Technology on Communication Information Security Control Laboratory JiaxingZhejiangChina314033 Huawei Technologies Co. Ltd Shenzhen Guangdong China

ISBN: (纸本)9781665418133

A Ka-band quasi-elliptic bandpass filter (BPF) based on stereolithography apparatus (SLA) 3-D printing technique is proposed. The filter consists of four coupled resonators with three direct couplings between adjacent resonators and a cross coupling between the first and fourth resonators. Benefited from this feature, a pair of transmission zeros (TZs) can be produced in the stopband to enhance the passband selectivity significantly. Additionally, two waveguide bends are incorporated with the input and output waveguides to facilitate experimental test. For demonstration, a 3-D printed BPF prototype with center frequency of 30 GHz, bandwidth of 1.4 GHz, and return loss better than 20 dB is implemented and tested. The weight of the filter is 9.8 g only. The measured results demonstrate that the passband return loss is better than 10 dB, and the average in-band insertion loss is less than 2 dB.

关键词： Band-pass filters Printing Couplings Resonator filters Insertion loss Radar antennas Loss measurement

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Understanding the Dynamics of DNNs Using Graph Modularity

arXiv

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arXiv 2021年

作者： Lu, Yao Yang, Wen Zhang, Yunzhe Chen, Zuohui Chen, Jinyin Xuan, Qi Wang, Zhen Yang, Xiaoniu Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China Northwestern Polytechnical University Xi’an710072 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

There are good arguments to support the claim that deep neural networks (DNNs) capture better feature representations than the previous hand-crafted feature engineering, which leads to a significant performance improvement. In this paper, we move a tiny step towards understanding the dynamics of feature representations over layers. Specifically, we model the process of class separation of intermediate representations in pre-trained DNNs as the evolution of communities in dynamic graphs. Then, we introduce modularity, a generic metric in graph theory, to quantify the evolution of communities. In the preliminary experiment, we find that modularity roughly tends to increase as the layer goes deeper and the degradation and plateau arise when the model complexity is great relative to the dataset. Through an asymptotic analysis, we prove that modularity can be broadly used for different applications. For example, modularity provides new insights to quantify the difference between feature representations. More crucially, we demonstrate that the degradation and plateau in modularity curves represent redundant layers in DNNs and can be pruned with minimal impact on performance, which provides theoretical guidance for layer pruning. Our code is available at https://***/yaolu-zjut/Dynamic-Graphs-Construction. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum

arXiv

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arXiv 2022年

作者： Wang, Jinhuan Chen, Pengtao Xu, Xinyao Wu, Jiajing Shen, Meng Xuan, Qi Yang, Xiaoniu Institute of Cyberspace Security College of Information Engineering Zhejiang University of Technology Hangzhou310023 China School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China Shenzhen518066 China PCL Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518000 China Utron Technology Company Ltd. Hangzhou310056 China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

Due to the decentralized and public nature of the Blockchain ecosystem, the malicious activities on the Ethereum platform impose immeasurable losses for the users. Existing phishing scam detection methods mostly rely only on the analysis of original transaction networks, which is difficult to dig deeply into the transaction patterns hidden in the network structure of transaction interaction. In this paper, we propose a Transaction SubGraph Network (TSGN) based phishing accounts identification framework for Ethereum. We first extract transaction subgraphs for target accounts and then expand these subgraphs into corresponding TSGNs based on the different mapping mechanisms. In order to make our model incorporate more important information about real transactions, we encode the transaction attributes into the modeling process of TSGNs, yielding two variants of TSGN, i.e., Directed-TSGN and Temporal-TSGN, which can be applied to the different attributed networks. Especially, by introducing TSGN into multi-edge transaction networks, the Multiple-TSGN model proposed is able to preserve the temporal transaction flow information and capture the significant topological pattern of phishing scams, while reducing the time complexity of modeling large-scale networks. Extensive experimental results show that TSGN models can provide more potential information to improve the performance of phishing detection by incorporating graph representation learning. Copyright © 2022, The Authors. All rights reserved.

关键词： Topology

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Joint Delay and Maintenance Optimization for Spectrum Handoff in Cognitive Radio Networks Using Binary Shuffled Frog Leaping Algorithm 19

Joint Delay and Maintenance Optimization for Spectrum Handof...

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19th IEEE International Conference on communication technology, ICCT 2019

作者： Jiang, Jianjun Zheng, Shilian Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781728105352

In cognitive radio networks, when a primary user reoccupies the channel, cognitive radios (CRs) need to vacate the channel and reestablish a link on some other channel to avoid interference to primary users, resulting in spectrum handoff. A joint spectrum handoff delay and link maintenance optimization problem for spectrum handoff is formulated in this paper. A binary shuffled frog leaping algorithm (SFLA) based algorithm is proposed to solve this problem. Simulations show that the proposed algorithm performs far better than random target channel visiting scheme. It can obtain solutions with low handoff delay and low probability of handoff failure which are very close to the optimal solutions. © 2019 IEEE.

关键词： Cognitive radio

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Modulation Recognition of Underwater Acoustic communication Signals Based on Joint Feature Extraction

Modulation Recognition of Underwater Acoustic Communication ...

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2019 IEEE International Conference on Signal, information and Data Processing, ICSIDP 2019

作者： Ge, Yizhou Zhang, Xin Zhou, Qing Science and Technology on Communication Information Security Control Laboratory Jiaxing314000 China No.36 Research Institute of CETC Jiaxing314000 China School of Marine Science and Technology Northwestern Polytechnical University Xi'an710072 China

ISBN: (纸本)9781728123455

Recently, the research on modulation identification of underwater acoustic (UWA) communication signals has attracted much attention. It is a challenge to identify the modulation of underwater acoustic communication signals in the environment of low signal-to-noise ratio (SNR), multipath interference, frequency and phase drift. In this paper, a joint feature extraction algorithm is proposed which combines the method of cyclic spectrum with high-order cumulant to perform the modulation recognition of UWA communication. In the algorithm, the higher-order cumulant features of the communication signals and their counterparts after the square transformation are used firstly for the intra-class modulation recognition of phase shift keying (PSK) and frequency shift keying (FSK), and the inter-class modulation recognition of PSK. Then the cross-section parameter of spectral correlation function of signals are used for inter-class recognition of FSK modulation. Simulation results show that BPSK, QPSK, 2FSK and 4FSK underwater acoustic communication signals can be identified at rate better than 90% by using the joint modulation recognition algorithm with a signal-to-noise ratio of -2dB. © 2019 IEEE.

关键词： Underwater acoustic communication

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Defend Against Jamming Attacks Using Deep Reinforcement Learning

Defend Against Jamming Attacks Using Deep Reinforcement Lear...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Weiguo Shen Wei Wang Hu Jin Weifeng Zhang Science and Technology on Communication Information Security Control Laboratory China National University of Defense Technology China Jiaxing University China Jiaxing Deep Intelligence Technology Co. LTD China

ISBN: (纸本)9781665418133

Cognitive radio network has the learning ability to adjust transmission behavior to adapt to dynamic electromagnetic environment, and it has become a research hotspot in the field of the new generation of intelligent wireless communication systems. However, recent research results show that cognitive radio networks are vulnerable to interference attacks, resulting in a serious decline in spectrum utilization. In this paper, an intelligent anti-jamming scheme based on deep reinforcement learning is proposed, and the anti-jamming decision of the communication party is modeled as a Markov decision chain. This method can help the communication transmitter to learn a combination of communication parameters that can maximize the probability of communication success. In the specific implementation, we use Double DQN as the communication decision-making brain, and specially designed a convolutional neural network suitable for the communication spectrum as input to accurately estimate the action value function. The simulation results show that our method has better performance than the traditional anti-jamming method based on reinforcement learning.

关键词： Simulation Radio transmitters Reinforcement learning Interference Games Markov processes Brain modeling

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An Optimized Method of Packet Loss Rate under Backup Path Protection in OBS Network

引用

Journal of Physics: Conference Series 2021年第1期1746卷

作者： Aodong Meng Yucheng Chen Jiahao Dai Yongqun Chen Science and Technology on Communication Information Security Control Laboratory Jiaxing China No.36 Research Institute of CETC Jiaxing China

In order to calculate the packet loss rate in OBS network, this paper proposes a method, which performs good in both accuracy and rapidity, based on Erlang B formula to estimate the packet loss probability in OBS network using backup path protection mechanism. This method can be used to optimize the design of OBS network protocol, and it also provides an accurate and efficient approximate calculation method of packet loss rate in OBS network and can be conductive to the study of using copy transmission to enhance the network survivability. Based on the formula of Erlang B, this paper briefly introduces the derivation process and principle of this method. The basic experimental principles of simulation and estimation processes are designed in this paper, and the experimental results of the proposed method under a typical network topology (ARPA network) with no protection mechanism and 1 and 2 backup paths protection mechanisms are analyzed to verify its rapidity and accuracy. The results of experiments show the accuracy and efficiency of this method.

关键词：

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Distributed Blanket Jamming Resource Scheduling for Satellite Navigation Based on Particle Swarm Optimization and Genetic Algorithm 20

Distributed Blanket Jamming Resource Scheduling for Satellit...

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20th IEEE International Conference on communication technology, ICCT 2020

作者： Luo, Zhaoyi Deng, Min Yao, Zhiqiang Leng, Xiaofan Chen, Yongqi Information Security Control Laboratory Science and Technology on Communication Jiaxing China Xiangtan University's Centre for Intelligent Navigation and Remote Sensing Research Xiangtan China Xiangtan University Xiangtan China

ISBN: (纸本)9781728181417

Jamming technology for satellite navigation has been widely used in some fields. The distributed jamming system contains a large number of jamming sources. How to schedule the limited resources efficiently to fully utilize their operational effectiveness is important in distributed jamming for satellite navigation. Most of the existing studies about jamming for satellite navigation only pay attention to the jamming benefits, ignoring the jamming cost. We introduce the concept of jamming cost for satellite navigation. Firstly, we propose a method to evaluate jamming benefit for satellite navigation based on the principle of navigation signal processing of the receiver. Secondly, we analyze the overall benefit and cost of jamming resource scheduling countermeasures in two different scenarios for satellite navigation. Then we establish two multi-constrained resource scheduling model that maximizes jamming benefit and minimizes jamming cost. The particle swarm optimization (PSO) and the genetic algorithm (GA) are applied to solve the problem. Simulation results show that the performance of GA and PSO is better than traditional Simulated Annealing (SA) in two different scenarios. In both one-to-one and many-to-one scenarios, the GA can achieve better objective value but with a little longer time than the SA. While the PSO finds a little better objective value with shorter time than the SA. In conclusion, the GA is not easier to fall into local optimal solution. And the solution speed of the PSO is faster than the SA. © 2020 IEEE.

关键词： Simulated annealing

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Quantum proof and high-speed privacy amplification for quantum key distribution

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Physical Review Applied 2025年第5期23卷 054004-054004页

作者： Bing-Qi Yan Jun-Bin Wu Fan Fan Bing-Jie Xu Xiao-Ling Zhang Min Gu Key Laboratory of Atomic and Subatomic Structure and Quantum Control (Ministry of Education) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter School of Physics South China Normal University Guangzhou 510006 China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials Guangdong-Hong Kong Joint Laboratory of Quantum Matter South China Normal University Guangzhou 510006 China Quantum Science Center of Guangdong-HongKong-Macao Greater Bay Area (Guangdong) Shenzhen 518000 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu 611731 China National Key Laboratory of Security Communication Institute of Southwestern Communication Chengdu 610041 China

Privacy amplification (PA) is a vital step in the postprocessing stage of quantum key distribution, which can extract a secure key from a source partially leaked to the environment. We propose a PA scheme that uses the square hash (SQH)–modular arithmetic hash (MH) function. In consideration of a potential quantum attacker, we use the trace distance as a metric to measure the closeness between two classical-quantum states. We transform a raw key state to a processed state using this scheme and derive the trace distance between the processed state and the ideal target state. It is proven that the trace distance can be reached as small as desired. Additionally, our approach accelerates the SQH-MH function through the number-theoretic transform, reducing the computational complexity to O(nlog n). On the basis of a CPU, a maximum throughput rate of 1.06 Gbit/s is achieved, and the results show that our algorithm demonstrates good stability of the throughput rate when handling tasks with different compression ratios.

关键词： Number theory

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