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Pulse compression;designing and generating chirplet signal on FPGA

AIP Conference Proceedings 2022年第1期2386卷

作者： Mohammed Abdulbasit Alzaki Zainab Sabah Idan 1Department of Communication Techniques Engineering Faculty of Communication system Ministry of Education General Directorates Vocational Educations Al Najaf Iraq 2Department of Computer Techniques Engineering Faculty of Technical Engineering Alkafeel University Najaf Iraq

The electronics and telecommunications industries are constantly growing. The growth of the electronics and telecommunications industries poses new challenges for researchers and industrialists. One of these challenges is to generate the signal with the required bandwidth over a period of time that is used in various fields, especially radar systems. In short, to improve radar range resolution while achieving good SNR, it is necessary to reduce the signal width and increase the peak power. But there are cases such as Phased array radars that use solar cells and millimeter wave radars where the peak power cannot be increased, in which case the pulse compression technique is suggested as a solution. According to a common definition, pulse compression is a process performed on a wide pulse to turn it into a narrow pulse. In this paper, an attempt has been made to implement the signal compression steps in a practical way using FPGA. In order to achieve a signal with the possibility of better detection in the receiver, in this study, in addition to frequency modulation (Chirp signal), using a suitable architecture, amplitude modulation is performed on the generated signal (Chirplet signal). Simply put, if the chirp signal is designed in such a way that in addition to the frequency changes, the signal amplitude also changes over time, we get a model of the signal called the Chirplet. The main advantage of using the Chirplet signal is the reduction of unwanted frequencies entering the system due to the sudden avoidance of increasing and decreasing the initial and final sides of the signal. This ultimately makes it possible to detect the return signal with higher quality and accuracy. The FPGA under review is from the Spartan 6 xc6slx9 family. The simulation results show the production of compressed signal with the desired quality so that the ISLR and PSLR parameters for the final generated signal are obtained −7.5 and −14.5 respectively. In summary, according to the result

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Information Freshness in A Dual Monitoring system

Information Freshness in A Dual Monitoring System

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GLOBECOM 2022 - 2022 IEEE Global communications Conference

作者： Dapeng Deng Zhengchuan Chen Howard H. Yang Nikolaos Pappas Limei Hu Min Wang Yunjian Jia Tony Q.S. Quek School of Microelectronics and Communication Engineering Chongqing University Chongqing China National Mobile Communications Research Laboratory Southeast University Nanjing China Zhejiang University/University of Illinois at Urbana-Champaign Institute Zhejiang University Haining China Department of Computer and Information Science Linkoping University Linkoping Sweden School of Optoelectronics Engineering Chongqing University of Posts and Telecommunications Chongqing China Information System Technology and Design Pillar Singapore University of Technology and Design Singapore

ISBN: (纸本)9781665435413

We study the average age of information (AoI) and peak AoI (PAoI) of a dual-queue status update system that monitors a common stochastic process. We capture the state transition characteristics of the considered system by establishing a Markov chain. Using the state flow graph analysis method, we derive closed-form expressions of the average peak age of information (PAoI) and the average age of information (AoI) for the dual-queue update system. The numerical results show that compared with the single-queue update system, the average PAoI of the dual-queue update system is reduced by 33.5% and the average AoI dropped by 37.5%.

关键词： Closed-form solutions Markov processes Reliability theory Information age Sensor systems Real-time systems Sensors

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ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold

arXiv

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arXiv 2022年

作者： Wang, Muhan Zhang, Zhe Qiu, Xiaolan Gao, Silin Wang, Yue Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology China Suzhou Aerospace Information Research Institute Jiangsu Suzhou China Aerospace Information Research Institute Chinese Academy of Sciences China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China Electrical and Computer Engineering Department George Mason University FairfaxVA United States

Tomographic SAR technique has attracted remarkable interest for its ability of three-dimensional resolving along the elevation direction via a stack of SAR images collected from different cross-track angles. The emerged compressed sensing (CS)-based algorithms have been introduced into TomoSAR considering its super-resolution ability with limited samples. However, the conventional CS-based methods suffer from several drawbacks, including weak noise resistance, high computational complexity, and complex parameter fine-tuning. Aiming at efficient TomoSAR imaging, this paper proposes a novel efficient sparse unfolding network based on the analytic learned iterative shrinkage thresholding algorithm (ALISTA) architecture with adaptive threshold, named Adaptive Threshold ALISTA-based Sparse Imaging Network (ATASI-Net). The weight matrix in each layer of ATASI-Net is pre-computed as the solution of an offline optimization problem, leaving only two scalar parameters to be learned from data, which significantly simplifies the training stage. In addition, adaptive threshold is introduced for each azimuth-range pixel, enabling the threshold shrinkage to be not only layer-varied but also element-wise. Moreover, the final learned thresholds can be visualized and combined with the SAR image semantics for mutual feedback. Finally, extensive experiments on simulated and real data are carried out to demonstrate the effectiveness and efficiency of the proposed method. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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Master equations and quantum trajectories for squeezed wave packets

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Physical Review A 2022年第2期105卷 023721-023721页

作者： Jonathan A. Gross Ben Q. Baragiola T. M. Stace Joshua Combes Institut Quantique Université de Sherbrooke Sherbrooke Quebec Canada J1K 2R1 Center for Quantum Information and Control University of New Mexico Albuquerque New Mexico 87131-0001 USA Yukawa Institute for Theoretical Physics Kyoto University Kitashirakawa Oiwakecho Sakyo-ku Kyoto 606-8502 Japan Centre for Quantum Computation and Communication Technology School of Science RMIT University Melbourne Victoria 3000 Australia ARC Centre for Engineered Quantum System Department of Physics University of Queensland Brisbane Queensland 4072 Australia Department of Electrical Computer and Energy Engineering University of Colorado Boulder Boulder Colorado 80309 USA

The interaction between matter and squeezed light has mostly been treated within the approximation that the field-correlation time is small. Methods for treating squeezed light with more general correlations currently involve explicitly modeling the systems producing the light. We develop a general purpose input-output theory for a particular form of narrowband squeezed light, a squeezed wave-packet mode, that only concerns the statistics of the squeezed field and the shape of the wave packet. This formalism allows us to derive the input-output relations and the master equation. We also consider detecting the scattered field using photon counting and homodyne measurements, which necessitates the derivation of the stochastic master equation. The non-Markovian nature of the field manifests itself in the master equation as a coupled hierarchy of equations. We illustrate these with consequences for the decay and resonance fluorescence of two-level atoms in the presence of such fields.

关键词： Open quantum systems Squeezing of quantum noise Stochastic processes

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Energy Management and Trajectory Optimization for UAV-Enabled Legitimate Monitoring systems

arXiv

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arXiv 2020年

作者： Hu, Shuyan Wu, Qingqing Wang, Xin State Key Laboratory of ASIC and System School of Information Science and Technology Fudan University Shanghai200433 China Department of Electrical and Computer Engineering National University of Singapore Singapore119077 Singapore State Key Laboratory of ASIC and System Shanghai Institute for Advanced Communication and Data Science Department of Communication Science and Engineering Fudan University Shanghai200433 China

Thanks to their quick placement and high flexibility, unmanned aerial vehicles (UAVs) can be very useful in the current and future wireless communication systems. With a growing number of smart devices and infrastructure-free communication networks, it is necessary to legitimately monitor these networks to prevent crimes. In this paper, a novel framework is proposed to exploit the flexibility of the UAV for legitimate monitoring via joint trajectory design and energy management. The system includes a suspicious transmission link with a terrestrial transmitter and a terrestrial receiver, and a UAV to monitor the suspicious link. The UAV can adjust its positions and send jamming signal to the suspicious receiver to ensure successful eavesdropping. Based on this model, we first develop an approach to minimize the overall jamming energy consumption of the UAV. Building on a judicious (re)formulation, an alternating optimization approach is developed to compute a locally optimal solution in polynomial time. Furthermore, we model and include the propulsion power to minimize the overall energy consumption of the UAV. Leveraging the successive convex approximation method, an effective iterative approach is developed to find a feasible solution fulfilling the Karush-Kuhn-Tucker (KKT) conditions. Extensive numerical results are provided to verify the merits of the proposed schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Game-based Learning Approach to Cybersecurity

Game-based Learning Approach to Cybersecurity

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IEEE Education engineering (EDUCON)

作者： Llanos Tobarra Antonio Pérez Trapero Rafael Pastor Antonio Robles-Gómez Roberto Hernández Andrés Duque Jesús Cano Communication and Control System Department Spanish National Distance University (UNED) Madrid Spain Student Computer Science Engineering School Spanish National Distance University (UNED) Madrid Spain

ISBN: (数字)9781728109305

ISBN: (纸本)9781728109312

The inclusion of practical activities to train critical thinking skills is very relevant in the case of engineering subjects. In particular, it becomes a key element in the context of cybersecurity, as our case is. Therefore, this paper analyses a gambling experience in a cybersecurity subject within a computer engineering degree, in order to assess whether the spaced learning methodology contributes to the improvement of learning. The gamification experience is carried out through a Flag Capture Competition (CTF) among the enrolled students in the course. The use of the platform has also been evaluated in an exploratory way.

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Anomaly detection of time series with smoothness-inducing sequential variational auto-encoder

arXiv

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arXiv 2021年

作者： Li, Longyuan Yan, Junchi Wang, Haiyang Jin, Yaohui State Key Lab of Advanced Optical Communication System and Network MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai200240 China Department of Computer Science and Engineering MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai200240 China

Deep generative models have demonstrated their effectiveness in learning latent representation and modeling complex dependencies of time series. In this paper, we present a Smoothness-Inducing Sequential Variational Auto-Encoder (SISVAE) model for robust estimation and anomaly detection of multi-dimensional time series. Our model is based on Variational Auto-Encoder (VAE), and its backbone is fulfilled by a Recurrent Neural Network to capture latent temporal structures of time series for both generative model and inference model. Specifically, our model parameterizes mean and variance for each time-stamp with flexible neural networks, resulting in a non-stationary model that can work without the assumption of constant noise as commonly made by existing Markov models. However, such a flexibility may cause the model fragile to anomalies. To achieve robust density estimation which can also benefit detection tasks, we propose a smoothness-inducing prior over possible estimations. The proposed prior works as a regularizer that places penalty at non-smooth reconstructions. Our model is learned efficiently with a novel stochastic gradient variational Bayes estimator. In particular, we study two decision criteria for anomaly detection: reconstruction probability and reconstruction error. We show the effectiveness of our model on both synthetic datasets and public real-world benchmarks. © 2021, CC BY.

关键词： Recurrent neural networks

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Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

arXiv

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arXiv 2021年

作者： Li, Longyuan Zhang, Jihai Yan, Junchi Jin, Yaohui Zhang, Yunhao Duan, Yanjie Tian, Guangjian MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China State Key Lab of Advanced Optical Communication System and Network Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Huawei Noah’s Ark Lab China

Time-series is ubiquitous across applications, such as transportation, finance and healthcare. Time-series is often influenced by external factors, especially in the form of asynchronous events, making forecasting difficult. However, existing models are mainly designated for either synchronous time-series or asynchronous event sequence, and can hardly provide a synthetic way to capture the relation between them. We propose Variational Synergetic Multi-Horizon Network (VSMHN), a novel deep conditional generative model. To learn complex correlations across heterogeneous sequences, a tailored encoder is devised to combine the advances in deep point processes models and variational recurrent neural networks. In addition, an aligned time coding and an auxiliary transition scheme are carefully devised for batched training on unaligned sequences. Our model can be trained effectively using stochastic variational inference and generates probabilistic predictions with Monte-Carlo simulation. Furthermore, our model produces accurate, sharp and more realistic probabilistic forecasts. We also show that modeling asynchronous event sequences is crucial for multi-horizon time-series forecasting. © 2021, CC BY.

关键词： Time series

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Comprehensive Analysis of Secure Data Aggregation Scheme for Industrial Wireless Sensor Network

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computers, Materials & Continua 2019年第8期61卷 583-599页

作者： Weidong Fang Wuxiong Zhang QianQian Zhao Xiaohong Ji Wei Chen Biruk Assefa Key Laboratory of Wireless Sensor Network&Communication Shanghai Institute of Micro-system and Information TechnologyChinese Academy of SciencesShanghai201899China Shanghai Research Center for Wireless Communication Shanghai201210China College of Physics and Electronic Information Engineering Qinghai University for NationalitiesXining810007China School of Computer Science and Technology China University of Mining and TechnologyXuzhou221116China Infromation Communication Technology Department Wollo UniversityDessie EthiopiaEthiopia

As an Industrial Wireless Sensor Network(IWSN)is usually deployed in a harsh or unattended environment,the privacy security of data aggregation is facing more and more ***,the data aggregation protocols mainly focus on improving the efficiency of data transmitting and aggregating,alternately,the aim at enhancing the security of *** performances of the secure data aggregation protocols are the trade-off of several metrics,which involves the transmission/fusion,the energy efficiency and the security in Wireless Sensor Network(WSN).Unfortunately,there is no paper in systematic analysis about the performance of the secure data aggregation protocols whether in IWSN or in *** consideration of IWSN,we firstly review the security requirements and techniques in WSN data aggregation in this ***,we give a holistic overview of the classical secure data aggregation protocols,which are divided into three categories:hop-by-hop encrypted data aggregation,end-to-end encrypted data aggregation and unencrypted secure data *** this way,combining with the characteristics of industrial applications,we analyze the pros and cons of the existing security schemes in each category qualitatively,and realize that the security and the energy efficiency are suitable for ***,we make the conclusion about the techniques and approach in these categories,and highlight the future research directions of privacy preserving data aggregation in IWSN.

关键词： Industrial wireless sensor network wireless sensor network cyber security secure data aggregation protocol

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A wideband wearable antenna using DGS method with bending and wet performance analysis at sub-6 GHz 5G band

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AIP Conference Proceedings 2024年第1期3161卷

作者： S. K. Noor R. Nurulazlina C. H. C. Alexander T. Islam Advanced Communication Engineering (ACE) Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Malaysia Centre for Advanced Electrical & Electronic System (CAEES) Faculty of Engineering Built Environment and Information Technology SEGi University 47610 Petaling Jaya Selangor Malaysia Asia Pacific University of Technology and Innovation School of Engineering Jalan Teknologi 5 Taman Teknologi Malaysia 57000 Kuala Lumpur Malaysia Department of Electrical and Computer Engineering University of Houston Texas USA

In this paper, it introduces a compact (44mm x 50mm) wearable antenna made of fabric that operates within the sub-6 GHz range for 5G New Radio technology. The concept of Defected Ground Structure (DGS) was implemented to achieve wider bandwidth. The antenna relies on a felt textile base with a relative permittivity of 1.45 and a thickness of 3 millimeters. This base is then sandwiched between two layers of a special electrically conductive fabric called “Super shield it” for the ground and radiating planes. This new antenna design offers several advantages over similar wearable antennas for sub-6 GHz 5G. Unlike previous designs, this antenna maintains high performance even when bent or wet, making it more durable for real-world use. Moreover, the simulated bandwidth obtained was 140 MHz (3.42 to 3.56 GHz) at frees space flat condition and measured bandwidth was 1700 MHz which covers n77 and n78 band of the sub-6 GHz. The proposed antenna obtained an overall simulated gain of 2.67 dBi and directivity of 7.15 dBi when placed on the four-layer human phantom. The proposed wearable antenna covered the desired frequency range when subjected to bending, partially wet and fully wet. Lastly, the obtained Specific Absorption Rate (SAR) is 0.106 W/Kg which makes the proposed antenna safe to be used for body- centric communication.

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