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International Conference on Advanced communication technology (ICACT)

作者： Huijie Zhu Wei Xu Yalou Sang Zhiqiang Yao Limei Liu Moses C. Okonkw Science and Technology on Communication Information Security Control Laboratory Jiaxing Zhejiang China Changsha Technology Research Institute of Beidou Industry Safety Changsha Hunan China People's Liberation Army of China PLA92126 Fuzhou Fujian China School of Automation and Electronic Information Xiangtan University Xiangtan Hunan China

ISBN: (数字)9791188428069

ISBN: (纸本)9781665447027

At present, the satellite navigation and positioning system can provide a high precision positioning service to end users in outdoor environments. But in urban canyons, high-rise buildings, urban tunnels, tree canopy covered areas, and other environments with weak signal such as military base and other special places with signal disturbance or spoofery, effective positioning or positioning results cannot to be trusted. Hence, it is very important and meaningful to use the existing radio signals (“signal of opportunity”) in the environment for positioning. Among the existing types of signals, mobile communication signals have more obvious characteristics for signal of opportunity navigation and thus has received more attention. This paper aims to solve the problem of signal selection in the application of mobile communication signals to navigation and positioning. This done by using characteristics such as signal carrier frequency, received signal strength and geometric position distribution to model, evaluate and systematically analyze the influence of each factor on positioning performance. Finally, based on a comprehensive evaluation method, a signal selection algorithm is designed while putting the signal type, signal carrier frequency, received signal strength, geometric position of the signal source and other factors into consideration. GSM and LTE signals are used in an actual environment to analyze, verify and extract the parameters required for the selection algorithm, also a comparative verification analysis was carried out with cluster and sub-optimal selection algorithm. The positioning accuracy of the proposed model proves both the reliability and the effectiveness of the proposed algorithm for comprehensive evaluation of signal source selection.

关键词： Analytical models Software algorithms Clustering algorithms Radio navigation Vegetation Mobile communication Software

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

Distributed Blanket Jamming Resource Scheduling for Satellit...

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International Conference on communication technology (ICCT)

作者： Zhaoyi Luo Min Deng Zhiqiang Yao Xiaofan Leng Yongqi Chen Science and Technology on Communication Information Security Control Laboratory Jiaxing China Xiangtan University Xiangtan China Navigation and Remote Sensing Research Xiangtan University’s Centre for Intelligent Xiangtan China Security Control Laboratory Science and Technology on Communication Information Jiaxing China Changsha Technology Research Institute of Beidou Industry Safety Changsha China

ISBN: (数字)9781728181417

ISBN: (纸本)9781728181424

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.

关键词： Jamming Satellite navigation systems Satellites Genetic algorithms Job shop scheduling Resource management Indexes

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Enhanced Competitive Swarm Optimizer for Multi-task Optimization 2020

Enhanced Competitive Swarm Optimizer for Multi-task Optimiza...

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Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition

作者： Wei Li Junqing Yuan Haonan Luo Zhou Lei Qingzheng Xu School of Computer Science and Engineering Xi'an University of Technology and Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China School of Computer Science and Engineering Xi'an University of Technology Xi'an China College of Information and Communication National University of Defense Technology Xi'an China

ISBN: (纸本)9781450387835

In the real world, many problems possess the high degree of similarity. Inspired by multifactorial inheritance model, evolutionary multi-task optimization paradigm is proposed to simultaneously solve multiple optimization problems. However, experimental results have revealed that the performance of multifactorial evolutionary algorithm deteriorates with negative knowledge transfer between uncorrelated tasks. To alleviate this issue, we proposed an enhanced competitive swarm optimizer to explore the generality of the multitasking paradigm. A new velocity update mechanism for losers is proposed to improve the search ability. Further, a mating approach is proposed to transfer implicit knowledge among tasks for generating offspring. Experimental and statistical analyses are performed on CEC2017 evolutionary multitask optimization competition. Results show that the proposed algorithm is competitive in comparison with other state-of-the-art multifactorial optimization algorithms.

关键词： Evolutionary multitasking competitive swarm optimizer evolutionary algorithms

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Data Link Modeling and Simulation Based on DEVS 19

Data Link Modeling and Simulation Based on DEVS

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Proceedings of the 2019 2nd International Conference on Signal Processing and Machine Learning

作者： Zhenxing Luo Lulu Zhao Wanyong Tian Dan Yang Yiyuan Chen Jiabin Yu Jianjun Li Science and Technology on Communication Information Security Control Laboratory Jiaxing China CETC Key Laboratory of Data Link Technology Xi'An China Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781450372213

The Discrete Event System (DEVS)[1] Specification provides a reference standard for the model design and simulation development of complex discrete event state system. It designs a formal mechanism to describe discrete event state, which is composed of a set of strictly abstract mathematical symbols, and provides a strict description mechanism and execution logic for the modeling and Simulation of discrete event state system, it ensures the normalization, reusability and simulation operation ability of the model. As a special link system, Data Link[2] is different from general communication system. It is mainly used between different military platforms to ensure information sharing. By linking sensors, command and control system and weapon platform according to the specified message format and communication protocol, the information system that can automatically transmit the formatted data of battlefield situation, command and guidance, tactical coordination, weapon control, etc., in real time can form a close and efficient tactical link relationship between different combat platforms. In this paper, DEVS is used to simulate the Reporting Responsibility for Air, Surface, and Land tracks in MIL-STD-6016B.

关键词： DEVS Data Link ADEVS Modeling and Simulation

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GPU-Accelerated Multipath Clutter Cancellation Algorithm for DTMB-Based Passive Radar

GPU-Accelerated Multipath Clutter Cancellation Algorithm for...

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information science, Parallel and Distributed Systems (ISPDS), International Conference on

作者： Zirong Bu Huijie Zhu Jiachuan Qian Science and Technology on Communication Information Security Control Laboratory Jiaxing China No. 36 Research Institute of China Electronics Technology Group Corporation Jiaxing China

ISBN: (数字)9781728196688

ISBN: (纸本)9781728196695

In order to extract the target echo in the monitoring channel, the direct wave and the clutter should be suppressed in the signal processing of the passive radar. The batch version of the Extensive Cancellation Algorithm (ECA-B) is an effective time-domain clutter cancellation algorithm that can suppress direct waves and multipath clutter. And it has better robustness than ECA. However, ECA-B is a computationally intensive algorithm. Therefore, the Graphic Processing Unit (GPU) accelerated ECA-B algorithm has been studied and implemented on GPU by exploring the parallelism of the ECA-B algorithm. The paper contains the description of the algorithm implementation and the performance results analysis of the measured data.

关键词： Testing Radar Parallel processing information science Graphics processing units Conferences

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Cooperative Reflection and Synchronization Design for Distributed Multiple-RIS communications

arXiv

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arXiv 2022年

作者： Zhao, Yaqiong Xu, Wei You, Xiaohu Wang, Ning Sun, Huan The National Mobile Communications Research Lab. Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China The Wireless Technology Laboratory Huawei Technologies Co. Ltd. Shanghai201206 China

To reap the promised gain achieved by distributed reconfigurable intelligent surface (RIS)-enhanced communications in a wireless network, timing synchronization among these metasurfaces is an essential prerequisite in practice. This paper proposes a unified framework for the joint estimation of the unknown timing offsets and the RIS channel parameters, as well as the design of cooperative reflection and synchronization algorithm for the distributed multiple-RIS communication. Considering that RIS is usually a passive device with limited capability of signal processing, the individual timing offset and channel gains of each hop of the RIS links cannot be directly estimated. To make the estimation tractable, we propose to estimate the cascaded channels and timing offsets jointly by deriving a maximum likelihood estimator. Furthermore, we theoretically characterize the Cramér-Rao lower bound (CRLB) to evaluate the accuracy of this estimator. By using the proposed estimator and the derived CRLBs, an efficient resynchronization algorithm is devised jointly at the RISs and the destination to compensate the multiple timing offsets. Based on the majorization-minimization framework, the proposed algorithm admits semi-closed and closed form solutions for the RIS reflection matrices and the timing offset equalizer, respectively. Simulation results verify that our theoretical analysis well matches the numerical tests and validate the effectiveness of the proposed resynchronization algorithm. Copyright © 2022, The Authors. All rights reserved.

关键词： Timing circuits

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UPPRESSO: Untraceable and Unlinkable Privacy-PREserving Single Sign-On Services

arXiv

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arXiv 2021年

作者： Guo, Chengqian Lin, Jingqiang Cai, Quanwei Wang, Wei Li, Fengjun Wang, Qiongxiao Jing, Jiwu Zhao, Bin State Key Laboratory of Information Security Institute of Information Engineering CAS China Data Assurance and Communication Security Research Center CAS China School of Cyber Security University of Science and Technology of China China School of Cyber Security University of Chinese Academy of Sciences China University of Kansas United States *** Silicon Valley R&D Center China

Single sign-on (SSO) allows a user to maintain only the credential at the identity provider (IdP), to login to numerous RPs. However, SSO introduces extra privacy threats, compared with traditional authentication mechanisms, as (a) the IdP could track all RPs which a user is visiting, and (b) collusive RPs could learn a user's online profile by linking his identities across these RPs. This paper proposes a privacy-preserving SSO system, called UPPRESSO, to protect a user's login activities against both the curious IdP and collusive RPs. We analyze the identity dilemma between the security requirements and these privacy concerns, and convert the SSO privacy problems into an identity transformation challenge. In each login instance, an ephemeral pseudo-identity (denoted as P IDRP ) of the RP, is firstly negotiated between the user and the RP. P IDRP is sent to the IdP and designated in the identity token, so the IdP is not aware of the visited RP. Meanwhile, P IDRP is used by the IdP to transform the permanent user identity IDU into an ephemeral user pseudo-identity (denoted as P IDU ) in the identity token. On receiving the identity token, the RP transforms P IDU into a permanent account (denoted as Acct) of the user, by an ephemeral trapdoor in the negotiation. Given a user, the account at each RP is unique and different from IDU, so collusive RPs cannot link his identities across these RPs. We build the UPPRESSO prototype on top of MITREid Connect, an open-source implementation of OIDC. The extensive evaluation shows that UPPRESSO fulfills the requirements of both security and privacy and introduces reasonable overheads. Copyright © 2021, The Authors. All rights reserved.

关键词： Privacy-preserving techniques

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

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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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