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Principles, Applications, and Challenges of Reconfigurable Intelligent Surface-Enabled Backscatter Communication: A Comprehensive Survey and Outlook

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IEEE communications Surveys and Tutorials 2024年

作者： Han, Shuai Wang, Jinming Li, Cheng Hossain, Ekram Harbin Institute of Technology Communications Research Center China Simon Fraser University School of Engineering Science Canada University of Manitoba Department of Electrical and Computer Engineering Winnipeg Canada

Backscatter communication (BackCom) networks are expected to provide ultra-low-power transmission and massive connectivity in future wireless communication systems. Nevertheless, the double-fading effect significantly reduces signal intensity and is a primary problem of modern BackCom systems. Reconfigurable Intelligent Surface (RIS) can artificially modify the wireless environment through numerous controllable reflecting elements. With the help of RIS, the desired signals in the BackCom procedure can be captured and reflected in the specified direction, which is able to alleviate the double-fading problem. Specifically, RIS can be a backscatter device to send information instead of a collaborator to enhance transmission, yielding the RIS-BackCom mechanism. However, a comprehensive review of this technique still needs to be made available, dramatically limiting its development. This paper presents the fundamental principles and functions of legacy BackCom systems, the RIS technique, and RIS-BackCom networks. Then, we discuss the system-level performance with different modulation and channel estimation approaches. Further, we introduce symbiotic radio (SR) networks developed from the RIS-BackCom technique. After that, we provide a survey on diverse optimization issues existing in the applications of RIS-BackCom networks. Finally, we envision emerging use scenarios, potential challenges, and possible solutions in future wireless communication networks. © 1998-2012 IEEE.

关键词： Channel estimation

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Design and Development of a Microcontroller Based Fingerprint-Attendance System 4

Design and Development of a Microcontroller Based Fingerprin...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Mbengwa, Kaloso Samikannu, Ravi Rohini, R. Begam, K.Maruliya Kanimozhi, G. Yahya, Abid Botswana International University of Science and Technology Department of Electrical and Communications Systems Engineering Palapye Botswana Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Ece Chennai India Vivekanandha College of Engineering for Women Department of Computer Science and Engineering Tiruchengode India Periyar Maniammai Institute of Science and Technology Department of Electrical and Electronics Engineering Thanjavur India Center for Smart Grid Technologies School of Electrical Engineering Vellore Institute of Technology Tamil Nadu Chennai India

ISBN: (纸本)9798331529635

In the modern era of rapidly advancing technology, organizations across various sectors are continuously seeking innovative solutions to enhance operational efficiency, streamline processes, and improve overall productivity. One area that significantly impacts these goals is the management of employee/student attendance. Traditional manual attendance tracking methods often lead to inaccuracies, inefficiencies, and increased administrative overhead. Recognizing this challenge, this proposal is to bring forth developing a microcontroller-based implementation of a Fingerprint-Based Attendance System. The system uses the power of biometric authentication to improve how attendance is recorded and managed. Firstly, this system provides real-time attendance tracking, reducing the delay in data processing and enabling immediate access to attendance records. Secondly, the proposed system ensures a high level of accuracy in attendance recording. Thirdly, this system promotes enhanced security. © 2024 IEEE.

关键词： Microcontrollers

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The performance of circularly polarized phased sub-array antennas for 5G laptop devices investigating the radiation effects

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Progress in Electromagnetics Research C 2021年 110卷 267-283页

作者： Mahmoud, Korany R. Baz, Abdullah Alhakami, Wajdi Alhakami, Hosam Montaser, Ahmed M. Department of Electronics and Communications Faculty of Engineering Helwan University Cairo Egypt National Telecommunications Regulatory Authority Ministry of Communication and Information Technology Giza Egypt Computer Engineering Department College of Computer and Information Systems Umm Al-Qura University Makkah Saudi Arabia Department of Computer Science College of Computer and Information Technology Taif University P. O. Box 11099 Taif21944 Saudi Arabia Department of Computer Science College of Computer and Information Techonogy Umm Al-Qura University Makkah21955 Saudi Arabia Electrical Engineering Department Sohag University Sohag Egypt

In this paper, the performance of circularly polarized (CP) adaptive sub-arrays integrated into 5G laptop device is investigated in the presence of a whole-body human phantom model. In addition, the radiation effect of the steered beam patterns has been analyzed by calculating the specific absorption rate distribution and temperature rise. In this target, a single-feed CP antenna element has been firstly designed to resonate at 28GHz with high realized gain and radiation efficiency. Then, 4 subarrays have been constructed in a rectangular configuration with four-elements for each sub-array. To let the study more realistic, a complete human model is considered to investigate the radiation effects. The measured reflection coefficient and realized gain results of the designed antenna element are found to be -30 dB and 7.82 dB, respectively, in the assigned frequency band. Likewise, the antennas sub-arrays have approximately kept the same impedance matching attitude with high insertion loss of -22 dB and a realized gain and radiation efficiency of 16.85 dB and 86%, respectively, on average. Furthermore, the sub-arrays scan patterns and coverage efficiency have been studied considering the existence of the human body in different scenarios. Regarding the RF exposure, the results show that the resultant maximum values of specific absorption rate and power density do not exceed 1.52 W/kg and 3.5W/m2, respectively, whereas the maximum exposure temperature in such a case is less than 2.8°C after 30 minutes and decreases to 0.5°C after a penetration depth of 3mm which reflects the possibility of safe use. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Radiation efficiency

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Optimal Charging Control and Incentivization Strategies for Electric Vehicles Considering Grid Dynamical Constraints

Optimal Charging Control and Incentivization Strategies for ...

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American Control Conference (ACC)

作者： Amit Kumer Podder Tomonori Sadamoto Aranya Chakrabortty Department of Electrical and Computer Engineering North Carolina State University Raleigh NC Department of Mechanical Engineering and Intelligent Systems The University of Electro-Communications Chofu Tokyo

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

We study how high charging rate demands from electric vehicles (EVs) in a power distribution grid may collectively cause its dynamic instability, and, accordingly, how a price incentivization strategy can be used to steer customers to settle for lesser charging rate demands so that these instabilities can be avoided. We pose the problem as a joint optimization and optimal control formulation. The optimization determines the optimal charging setpoints for EVs to minimize the $\mathcal{H}_{2}- \mathbf{norm}$ of the transfer function of the grid model, while the optimal control simultaneously develops a linear quadratic regulator (LQR) based state-feedback control signal for the battery currents of those EVs to jointly minimize the risk of grid instability. A subsequent algorithm is developed to determine how much customers may be willing to sacrifice their intended charging rate demands in return for financial incentives. Results are validated using numerical simulations of three EV charging stations in the IEEE 33-bus power distribution model.

关键词： Damping Regulators Optimal control Transfer functions Power distribution Numerical simulation Voltage control

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Implementation of remote AI farmer system

Implementation of remote AI farmer system

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IET International Conference on engineering Technologies and Applications (ICETA 2024)

作者： Ching-Ta Lu Yu-Han Weng Yun-En Wu Yi-Ching Wei Department of Communications Engineering Feng Chia University Taichung City Taiwan Department of Information Engineering and Computer Science Feng Chia University Taichung City Taiwan

ISBN: (数字)9781837242252

People need to pay more attention to planting and caring for plants. Orchids are an essential potted flower item in the global flower market as they are a highly economical flower production crop. Despite the increasing demand for orchids in the global market, the production of orchids has remained the same, which is attributed to the difficulty in caring for orchids and the high cost of human efforts. Therefore, this study chooses orchids as the target. We realize an orchid care system that can give users precise advice on fertilizer and pesticide application through AI assistance. The automatic light chasing system allows orchids to chase the light when the light is weak and avoid the light when the sun is intense; the humidity detection gives orchids an automatic humidity environment; and the wireless photography and identification allows farms to be identified and managed automatically. The application of this system can also be extended to other species of plants. Accordingly, the proposed system is scalable.

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Mask-CTC-based Encoder Pre-training for Streaming End-to-End Speech Recognition

arXiv

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arXiv 2023年

作者： Zhao, Huaibo Higuchi, Yosuke Kida, Yusuke Ogawa, Tetsuji Kobayashi, Tetsunori Department of Communications and Computer Engineering Waseda University Tokyo Japan LINE Corporation Tokyo Japan

Achieving high accuracy with low latency has always been a challenge in streaming end-to-end automatic speech recognition (ASR) systems. By attending to more future contexts, a streaming ASR model achieves higher accuracy but results in larger latency, which hurts the streaming performance. In the Mask-CTC framework, an encoder network is trained to learn the feature representation that anticipates long-term contexts, which is desirable for streaming ASR. Mask-CTC-based encoder pre-training has been shown beneficial in achieving low latency and high accuracy for triggered attention-based ASR. However, the effectiveness of this method has not been demonstrated for various model architectures, nor has it been verified that the encoder has the expected look-ahead capability to reduce latency. This study, therefore, examines the effectiveness of Mask-CTC-based pre-training for models with different architectures, such as Transformer-Transducer and contextual block streaming ASR. We also discuss the effect of the proposed pre-training method on obtaining accurate output spike timings, which contributes to the latency reduction in streaming ASR. © 2023, CC BY.

关键词： Speech recognition

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Sparse Channel Feedback for Energy-Efficient mmWave Massive MIMO Systems

Sparse Channel Feedback for Energy-Efficient mmWave Massive ...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Seungnyun Kim Jiao Wu Jihoon Moon Byonghyo Shim Department of Electrical and Computer Engineering Institute of New Media and Communications Seoul National University Korea

mmWave massive multi-input multi-output (MIMO) systems with large-scale antenna array have potential to increase the spectral efficiency by orders of magnitude. One well-known drawback of this systems is that the power consumption of base station (BS) is considerable. To improve the energy efficiency and throughput, it is crucial that the BS acquires accurate downlink channel state information (CSI). However, this task is difficult since the CSI feedback overhead scales linearly with the number of antennas. In this paper, we propose an approach to maximize the energy efficiency of mmWave massive MIMO systems using a sparse channel feedback. Key idea of the proposed scheme is to choose a small number paths among the whole propagation paths in the angular domain channel and then exploit the channel information of chosen paths in the data precoding. From the performance analysis and the numerical results, we demonstrate that the proposed scheme achieves considerable energy efficiency improvement and feedback overhead reduction over the conventional CSI feedback-based schemes.

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SaTrack: LoS/NLoS State-Aware WiFi Indoor Tracking System

SaTrack: LoS/NLoS State-Aware WiFi Indoor Tracking System

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IEEE communications Society Conference on Sensor and Ad Hoc communications and Networks (SECON)

作者： Yinnan Zhou Hao Zhou Luowei Li Siming Chen Zhi Liu Xiang-Yang Li LINKE Lab School of Computer Science and Technology University of Science and Technology of China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798331519186

ISBN: (纸本)9798331519193

WiFi-based technology is appealing for indoor localization due to the widely deployed infrastructures. Recently, path separation solutions have been proposed to address the multipath effects and achieve decimeter-level localization accuracy in line-of-sight (LoS) scenarios. However, these solutions experience serious performance degradation in non-line-of-sight (NLoS) scenarios, and couldn't be used for mobile device tracking where continuous LoS/NLoS switching happens. In this paper, we propose SaTrack, a LoS/NLoS state-aware mobile device tracking system. SaTrack identifies LoS/NLoS states based on the diversity of the strongest estimated paths when using different reference antennas. With the observation of spatial aggregation and temporal continuity for the Tx-Rx direct path, SaTrack chooses the direct path through two-step clustering, i.e., clustering in the spatial domain to form candidates and clustering again in the temporal domain to select the winner. Extensive experiments are conducted to evaluate the effectiveness of SaTrack. In a typical indoor environment with abundant multipath, SaTrack achieves 0.64m and 1.27m for the median and 90th percentile tracking errors, outperforming the state-of-the-art (SOTA) solutions.

关键词： Location awareness Performance evaluation Accuracy Line-of-sight propagation Switches Mobile handsets Sensors Indoor environment Wireless fidelity Antennas

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Mask-CTC-Based Encoder Pre-Training for Streaming End-to-End Speech Recognition

Mask-CTC-Based Encoder Pre-Training for Streaming End-to-End...

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European Signal Processing Conference (EUSIPCO)

作者： Huaibo Zhao Yosuke Higuchi Yusuke Kida Tetsuji Ogawa Tetsunori Kobayashi Department of Communications and Computer Engineering Waseda University Tokyo Japan LINE Corporation Tokyo Japan

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Multimodal biometric authentication based on deep fusion of electrocardiogram (ECG) and finger vein

Multimodal biometric authentication based on deep fusion of ...

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作者： El-Rahiem, Basma Abd El-Samie, Fathi E. Abd Amin, Mohamed Mathematics and Computer Science Department Faculty of Science Menoufia University Shebin El-Koom Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt

Biometric identification depends on the statistical analysis of the unique physical and behavioral characteristics of individuals. However, a unimodal biometric system is susceptible to different attacks such as spoof attacks. To overcome these limitations, we propose a multimodal biometric authentication system based on deep fusion of electrocardiogram (ECG) and finger vein. The proposed system has three main components, which are biometric pre-processing, deep feature extraction, and authentication. During the pre-processing, normalization and filtering techniques are adapted for each biometric. In the feature extraction process, the features are extracted using a proposed deep Convolutional Neural Network (CNN) model. Then, the authentication process is performed on the extracted features using five well-known machine learning classifiers: Support Vector Machine (SVM), K-Nearest Neighbors (KNNs), Random Forest (RF), Naive Bayes (NB), and Artificial Neural Network (ANN). In addition, to represent the deep features in a low-dimensional feature space and speed up the authentication task, we adopt Multi-Canonical Correlation Analysis (MCCA). We combine the two biometric systems based on ECG and finger vein into a single multimodal biometric system using feature and score fusion. The performance of the proposed system is tested on two finger vein (TW finger vein and VeinPolyU finger vein) databases and two ECG (MWM-HIT and ECG-ID) databases. Experimental results reveal improvement in terms of authentication performance with Equal Error Rates (EERs) of 0.12% and 1.40% using feature fusion and score fusion, respectively. Furthermore, the authentication with the proposed multimodal system using MCCA feature fusion with a KNN classifier shows an increase of accuracy by an average of 10% compared with those of other machine learning algorithms. Therefore, the proposed biometric system is effective in performing secure authentication and assisting the stakeholders in making

关键词： Authentication

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