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Energy-Efficient UAV Trajectory Design for Backscatter communication: A Deep Reinforcement Learning Approach

China communications 2020年第10期17卷 129-141页

作者： Yiwen Nie Junhui Zhao Jun Liu Jing Jiang Ruijin Ding School of Electronic and Information Engineering Beijing Jioatong UniversityBeijing 100044China School of Information Engineering East China Jiaotong UniversityNanchang 330013China Institute of Network Sciences and Cyberspace Tsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology(BNRist) Beijing 100084China Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts and TelecommunicationsXi’an 710121China Institute for Artificial Intelligence Tsinghua University(THUAI)Beijing 100084China State Key Laboratory of Intelligent Technologies and Systems Tsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology(BNRist) Department of AutomationTsinghua UniversityBeijing 100084China

Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and *** this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing ***,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among *** results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.

关键词： unmanned aerial vehicle(UAV) trajectory design backscatter communication deep reinforcement learning energy-efficient

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Example-based web page recoloring method

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Frontiers of Computer science 2020年第5期14卷 229-231页

作者： Yonghao Long Zhihao Zang Xiangping Chen Fan Zhou Xiaonan Luo School of Data and Computer Science National Engineering Research Center of Digital LifeSun Yat-sen UniversityGuangzhou510006China Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion The School of Communication and DesignSun Yat-sen UniversityGuangzhou510006China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China

1 Introduction The user interface(UI)is very important for a software product,and a well-designed UI will attract users and make a good *** has been shown that color plays an important role in invoking emotional reactions[1],influencing usability[2],forming first impressions[3],and affecting the energy cost of the UI[4].Generating satisfying color schemes has high requirements for experience,aesthetic,and creative inspiration of designers[5].

关键词： web coloring satisfying

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Federated Coordinate Descent for Privacy-Preserving Multiparty Linear Regression

arXiv

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arXiv 2022年

作者： Leng, Xinlin Li, Chenxu Xu, Weifeng Sun, Yuyan Wang, Hongtao School of Control and Computer Engineering North China Electric Power University Baoding071051 China School of Computer Science and Technology Shandong University of Finance and Economics Jinan250014 China Beijing Key Laboratory of IoT Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Hebei Key Laboratory of Knowledge Computing for Energy & Power Baoding071051 China

Federated linear regressions have been developed and applied in various domains, where multiparties collaboratively and securely perform optimization algorithms, e.g., Gradient Descent, to learn a set of optimal model weights. However, traditional Gradient-Descent based methods fail to solve problems which contain L1regularization in objective functions, such as lasso regression. In this paper, we present Federated Coordinate Descent, a new distributed scheme called FCD, to address this issue securely under multiparty scenarios. Specifically, through secure aggregation and noise perturbations, our scheme guarantees that: (1) no local information is leaked to other parties, and (2) global model weights are not exposed to cloud servers. The proposed FCD scheme fills the gap between multiparty secure learning and coordinate descent methods, and is applicable for general linear regressions, including linear, ridge, and lasso regressions. Theoretical analyses prove the security guarantees of our scheme against semi-honest attackers. Experimental results on three UCI datasets demonstrate that regressions under our FCD scheme are effective as centralized models. The performance evaluation on synthetic dataset also reveals that our scheme achieves efficient properties on computation cost and communication *** Codes 68Q32 Copyright © 2022, The Authors. All rights reserved.

关键词： Gradient methods

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Code rate estimation and code sequence retrieval of the binary phase-coded radar signal using further autocorrelation analysing

Code rate estimation and code sequence retrieval of the bina...

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2019 International Conference on communications, information System, and Computer Engineering, CISCE 2019

作者： Jiang, Bin Li, Jie Yang, Xiaohong Zhu, Jun Xiong, Ying Tang, Bin Science and Technology on Communication Information Security Control Laboratory 36th Research Institute of CETC Jiaxing China University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781728136813

The binary phase-coded radar signal code rate estimation and code sequence retrieval are important in EW and ELINT. In this paper, the statistical autocorrelation function of the binary phase-coded radar signal is studied in depth, and a code rate estimation and a code sequence retrieval method are proposed. With the signal symbol length rough estimation, the sampling points of calculating statistical autocorrelation function can be adaptively selected. Furthermore, exploring the valley points of the autocorrelation function envelope to detect the signal phase abrupt points, the signal code rate can be estimated and the code sequence can be recovered. Experimental results corroborate that the proposed method can effectively reduce the mean square errors of the code rate estimation and code sequence retrieval in low signal to noise ratio (SNR) conditions. © 2019 IEEE.

关键词： Mean square error

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Swing error phase modulation jamming method of airborne SAR

Swing error phase modulation jamming method of airborne SAR

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2019 International Conference on communications, information System, and Computer Engineering, CISCE 2019

作者： Li, Jie Jiang, Bin Liang, Wenyan Zhu, Jun Xiong, Ying Tang, Bin Science and Technology on Communication Information Security Control Laboratory 36th Research Institute of CETC Jiaxing China University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781728136813

A new airborne synthetic aperture radar (SAR) jamming-swing error phase modulation jamming is presented. The method uses the swing error of the line-of-sight SAR during the motion of the airborne SAR and modulate the phase error caused by the swing error to the radar signal received by the jammer to generate the jamming signal and transmit the jamming signal to the radar receiver. The effectiveness of this jamming method against the common motion error compensation algorithm-phase gradient autofocus (PGA) algorithm is analyzed. The simulation experiment verifies the correctness of the theoretical analysis. © 2019 IEEE.

关键词： Error compensation

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Bitstream protocol classification mechanism based on feature extraction

Bitstream protocol classification mechanism based on feature...

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2019 International Conference on Networking and Network Applications, NaNA 2019

作者： Wang, Wei Bai, Binbin Wang, Yichuan Hei, Xinhong Zhang, Li Science and Technology on Communication Information Security Control Laboratory No.36 Research Institution of CETC China College of Computer Science and Engineering Xi'An University of Technology Xi'an China

ISBN: (纸本)9781728126296

In recent years, with the continuous expansion of network communication scale, the types of niche protocols and various proprietary communication protocols are increasing day by day, but botnet and various network attacks have also emerged in endlessly. However, most of the commonly used network protocol recognition software uses a single method, and can only identify specific network data packets or data streams, the degree of automation is low, and the recognition accuracy is not high. In view of the above situation, this paper takes the bit flow protocol data frame as the research object, takes the multi-protocol recognition as the goal, and carries on the protocol feature recognition by comparing the data flow characteristics and the evaluation index. The features of the protocol to be detected are compared with the existing protocol features of the feature base, and the similarity between each protocol is judged. The extracted composite features are digitalized to generate 0-1 matrix, and clustering analysis is completed. The frame vector quantification algorithm of message data is designed and implemented to improve the clustering efficiency. The experimental results show that, compared with the traditional algorithm, the protocol eigenvector algorithm improves the accuracy by 15%, which can make the unknown protocol format be generated faster. © 2019 IEEE.

关键词： Network security

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Att-TCN: An Advertising Attribution Method Based on Temporal Convolutional Network with Attention Mechanism

Att-TCN: An Advertising Attribution Method Based on Temporal...

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International Conference on Computer and communications (ICCC)

作者： Bowen Xie Yi Sun Zhaowen Lin Baoquan Ma School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China National Engineering Laboratory for Mobile Network Technologies Beijing China National Computer System Engineering Research Institute of China Beijing China National Engineering Laboratory for Industry Control System Information Security Technology Beijing China

Advertising attribution is an effective method to measure the effect of various advertisements in the era of Internet advertising. It enables scientific tracking back and refined operation of advertising by quantitatively evaluating the contribution of different advertising channels to reach the target. It is challenging to predict conversion results based on users' journey data accurately, reflect the impact of ads on user conversions, and appropriately assign attribution values to advertising channels. To achieve the above objectives, we propose an advertising attribution method based on a temporal convolutional network with an attention mechanism (Att-TCN). By mining the hidden information in time and attribution channels using the attention mechanism, our proposed method can improve the accuracy of conversion prediction and thus more rationally assign attribution values across channels. Experimental validation on a real dataset obtained from an operational commercial advertising monitoring company shows that our proposed attribution method has better accuracy than other state-of-the-art attribution methods and gives an open-ended approach to attribution value assignment.

关键词： Target tracking Costs Companies Predictive models Internet Convolutional neural networks Data mining

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Demodnet: Learning soft demodulation from hard information using convolutional neural network

arXiv

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arXiv 2020年

作者： Zheng, Shilian Zhou, Xiaoyu Chen, Shichuan Qi, Peihan Yang, Xiaoniu Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China

Soft demodulation is a basic module of traditional communication receivers. It converts received symbols into soft bits, that is, log likelihood ratios (LLRs). However, in the non-ideal additive white Gaussian noise (AWGN) channel, it is difficult to accurately calculate the LLR. In this letter, we propose a demodulator, DemodNet, based on a fully convolutional neural network with variable input and output length. We use hard bit information to train the DemodNet, and we propose log probability ratio (LPR) based on the output layer of the trained DemodNet to realize soft demodulation. The simulation results show that under the AWGN channel, the performance of both hard demodulation and soft demodulation of DemodNet is very close to the traditional methods. In three non-ideal channel scenarios, i.e., the presence of frequency deviation, additive generalized Gaussian noise (AGGN) channel, and Rayleigh fading channel, the performance of channel decoding using the soft information LPR obtained by DemodNet is better than the performance of decoding using the exact LLR calculated under the ideal AWGN assumption. © 2020, CC-BY.

关键词： Demodulation

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A Spectrum Status Duration Prediction Method Based on Homotopy Theory for UAV communication 6

A Spectrum Status Duration Prediction Method Based on Homoto...

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6th IEEE International Conference on Computer and communications, ICCC 2020

作者： Zhou, Tao Luo, Shan Zheng, Peixiang Lin, Rongping School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781728186351

With the development of wireless communication technology, a large number of spectrum resources are occupied and become increasingly scarce. If drones want to communicate, they need to share spectrum with others. The method of spectrum prediction in cognitive radio can efficiently achieve this. The traditional spectrum status duration prediction method based on the non-stationary hidden Markov model only predict the duration of one fixed geographic location and cannot meet the requirement of UAV's communications. We intend to apply the homotopy theory to the non-stationary hidden Markov model to obtain the spectrum status duration of different locations so that it can apply to UAV's communications. We also conducted experiments to predict the duration of the spectrum status at different locations. The experimental results show that our model can work well. © 2020 IEEE.

关键词： Hidden Markov models

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A novel approach to reducing information leakage for quantum key distribution

arXiv

引用

arXiv 2021年

作者： Mao, Hao-Kun Zhao, Qiang Qiao, Yu-Cheng Yan, Bing-Ze Xu, Bing-Jie Abd El-Latif, Ahmed A. Li, Qiong Department of Computer Science and Technology Harbin Institute of Technology Harbin150080 China College of Software Engineering ZhengZhou University of Light Industry ZhengZhou450053 China Guangxi Key Lab Cryptography & Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China Science and Technology on Security Communication Laboratory Institute of Southwestern Communication Chengdu610041 China Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom Egypt

Quantum key distribution (QKD) is an important branch of quantum information science as it holds promise for unconditionally secure communication. For QKD research, a central issue is to improve the final secure key rate (SKR) and the maximal transmission distance. To address this issue, most works focused on reducing the information leakage of QKD. In this paper, we propose a novel approach to further reduce the information leakage by specially considering the overlap between the information leakage of quantum part and post-processing part. The overlap means that the information leakage of post-processing part caused solely by multi-photon pulses is considered twice in previous studies, i.e., both in quantum part and post-processing part. Since the information carried by multi-photon pulses has been considered as completely known by Eve through the photon-number-splitting attack in quantum part, there is no need to consider it in post-processing part repetitively during the SKR calculation. Therefore, our approach can theoretically reduce the information leakage of a QKD protocol. Based on this idea, we derive the formulas to calculate the amount of information leakage for decoy-BB84 and sending-or-not-sending twin-field protocols. Simulation results for these two typical protocols also demonstrate that our approach evidently improves the SKR as well as the maximal transmission distance under practical experimental parameters. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum cryptography

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