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Beamspace U-ESPRIT DOA Estimation Algorithm of Coherently Distributed Sources in Massive MIMO Systems

Beamspace U-ESPRIT DOA Estimation Algorithm of Coherently Di...

引用

International Workshop on advanced Computational Intelligence (IWACI)

作者： Yang Liu Lina Hou Qinmin Shen Cheng Lv Shun Na Tianshuang Qiu College of Electronic Information Engineering Inner Mongolia University Hohhot China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China

ISBN: (数字)9781728142487

ISBN: (纸本)9781728142494

The coherently distributed sources model is more suitable to support the DOA estimation for massive Multiple-Input Multiple-Output (MIMO) systems. Since a large number of antennas brings unbearable computing burden of the DOA estimation, we propose a low-complexity DOA estimation algorithm for coherently distributed sources by utilizing unitary ESPRIT in beamspace. Specifically, by choosing fewer beams in two-dimensional beamspace for DOA estimation, the dimension of the output vector decreases so that the complexity is greatly reduced. In addition, the U-ESPRIT algorithm is utilized in beamspace and the azimuth angle and the elevation angle are automatically coupled with low complexity. Moreover, the proof of rotation invariance and the analysis of complexity guarantee the feasibility of the proposed algorithm. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm for massive MIMO systems.

关键词： Direction-of-arrival estimation Estimation MIMO communication Complexity theory signal processing algorithms Discrete Fourier transforms Azimuth

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Calibration and direction of arrival estimation with a uniform circular array for mobile radio channels

Calibration and direction of arrival estimation with a unifo...

引用

IEEE conference on Vehicular Technology (VTC)

作者： J.L.M. Terres I. Gaspard J. Freese R. Jakoby Technologiezentrum T Systems Nova GmbH Berkom Darmstadt Germany Technische Universität Darmstadt Darmstadt Germany

By use of array antennas in mobile radio communications, a gain for the desired signal and more efficient rejection of interference can be achieved, either through diversity or beamforming techniques. Their use depends, basically, on the correlation coefficient between signals on the different array elements, that is influenced by the existence of direct line of sight (LOS). As yet, arrays are located only at the base station, but their use at the mobile station is also possible. In. this work, advanced direction of arrival (DOA) and delay estimation algorithms with a uniform circular array (UCA) located at the mobile station are analysed. These techniques demand a highly accurate calibration of the array to reduce the effects of both inter-element coupling and non-omni directional antenna pattern. On the basis of measurements in an anechoic room calibration is performed, and a unitary delay-DOA algorithm is adapted and implemented for circular arrays. The results obtained from a measurement campaign show that at a high percentage of locations the DOA of the first multipath component coincides with the direction towards the transmitter in azimuth. This result implies the use of array antennas also in mobile stations where enough space is available, e.g. on the roof of cars and trains.

关键词： Calibration Direction of arrival estimation Land mobile radio Antenna arrays Mobile antennas Antenna measurements Mobile communication Interference Array signal processing Base stations

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Development and Application of Transformer State Perception Terminals Based on Artificial Intelligence and Edge Computing

Development and Application of Transformer State Perception ...

引用

Energy Engineering and Power Systems (EEPS), International conference on

作者： Xintong Wang Xin Chen Xuexing Zhang Zhendong Tang State grid Jibei Electric Power Co. Ltd. Tangshan power supply company Tangshan China

ISBN: (数字)9798350366914

ISBN: (纸本)9798350366921

The arrival of the global digital and intelligent revolution has profoundly changed the fundamental structure and operational basis of various industries, making the energy transition and digital development of power systems an inevitable trend. However, the rapid development of sensor and communication technologies has increasingly highlighted the bottleneck in data processing capabilities. With the widespread installation of sensors, power equipment continuously generates massive amounts of state monitoring data, and traditional data analysis algorithms are unable to cope with the growing backlog of data. To address this challenge, this paper explores the feasibility of integrating advanced artificial intelligence technologies on the edge computing platform for efficient real-time processing and analysis at the data source. The paper focuses on the development and application of edge computing terminals for current transformer state perception. By analyzing the problems and challenges in the current operation and control of current transformers, an edge computing service framework suitable for current transformer state detection is constructed based on edge computing. In conjunction with actual application needs, this paper proposes effective edge computing implementation solutions. The research results show that this solution significantly improves data processing efficiency and accuracy, playing an important role in promoting the intelligent monitoring and maintenance of current transformers.

关键词： Current transformers Soft sensors Computational modeling Real-time systems Power systems Convolutional neural networks Artificial intelligence signal analysis Monitoring Edge computing

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Web App Design for Surface Plasmon Resonance signal processing

Web App Design for Surface Plasmon Resonance Signal Processi...

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International conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)

作者： Isa Anshori Mahendra Baleno Rama Rey Ezra Suksmandhira Harimurti Gilang Gumilar Muhammad Yusuf Silmina Prastriyati Sari Brian Yuliarto Wyanda Arnafia Lab-on-a-Chip Laboratory Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Bandung Indonesia Advanced Functional Materials Lab. Institut Teknologi Bandung Bandung Indonesia Research Center for Molecular Biotechnology and Bioinformatics Universitas Padjadjaran Bandung Indonesia PT. Tekad Mandiri Citra Bandung Indonesia

ISBN: (数字)9781728189222

ISBN: (纸本)9781728189239

The rapid spread of COVID-19 disturbs the availability of the diagnostic tests for detecting COVID-19. Recently, a new test method is being developed by the cooperation between BPPT, ITB, Unpad and PT. TMC. The method is called as the Surface Plasmon Resonance (SPR). However, the data output of the SPR device must be further processed to obtain a powerful information. Hence, we propose a new approach for interactively visualizing SPR data by designing a web app platform. By this platform, user/operator can directly upload the SPR data output file in the web app. In the current design, the imported data are stored in the cloud storage. Moreover, user can also enter additional data for the purpose of labelling the graph that will be automatically generated. Bokeh was chosen as a Python library for visualizing data into an interactive graph. The graph features are label, tooltips, and interactive legend. A SPR data can have various signal responses. But, the labels can be as the help to distinguish those responses. The tooltips allow the user to obtain detailed information from a data point. Meanwhile, the interactive legend is used to distinguish SPR data plot and baseline plot. Therefore, by the use of this web app, the SPR sample analysis could be done just within in minutes. It also only requires a web browser and Python to works.

关键词： Data visualization COVID-19 signal processing algorithms Libraries Surface plasmons Python Uniform resource locators

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Magnetic integrated passives for information and communication technology

Magnetic integrated passives for information and communicati...

引用

2017 IEEE International Magnetics conference, INTERMAG 2017

作者： Yamaguchi, M. Tanaka, S. Ma, J. Miyazawa, Y. Sato, M. Nishizawa, M. Nagata, M. Ishiyama, K. Kondo, K. Okiyoneda, Y. Department of Electrical Engineering Tohoku Unviersity Sendai Japan Tohoku University Sendai Japan Research Institute of Electrical Communication Tohoku University Sendai Japan Graduate School of Science Technology and Innovation Kobe University Kobe Japan Advanced Materials Research and Development Division NEC TOKIN Corp. Sendai Japan Engineering Development Sect. Showa Aircraft Industry Co. Ltd. Akishima Japan

ISBN: (纸本)9781538610862

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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OFDM waveform feature suppression

OFDM waveform feature suppression

引用

MILCOM, Military Communications conference

作者： R.R. Meyer M.N. Newhouse Communications & Navigation Systems Department Advanced Technology Center Rockwell Collins Cedar Rapids IA USA

Traditional multicarrier systems developed for commercial applications use features of the waveform to improve the performance of receiver processing. These features, added in transmit processing, include, for example, a cyclic extension to mitigate inter-block interference, pilot tones inserted to assess the channel state, and specific FFT bin patterns for synchronization. An adversary can exploit these features to glean information about the transmitted waveform. The paper discusses a low probability of intercept (LPI) analysis of traditional and militarized OFDM waveforms. Militarized efforts include the elimination of the cyclic extension, pilot tones, and fixed synchronization patterns. We present an overview of the algorithms used to provide additional LPI relative to the commercial systems. In addition, traditional LPI quantitative analyses of the OFDM waveform are presented. Without adding the militarized features, the analysis shows that the OFDM waveform is rather easily detected. These analyses show the detectable features in OFDM without cyclic extension decrease as the number of subcarriers increase.

关键词： Frequency synchronization Interference Computer vision Modulation coding OFDM modulation Delay effects signal generators Wideband Navigation Communications technology

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Machine Learning-based Spectrum Sensing Techniques for Optimized Spectrum Utilization in Cognitive Radio Networks

Machine Learning-based Spectrum Sensing Techniques for Optim...

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Advancement in Technology (ICONAT), International conference for

作者： Pavan Chaudhary Rajesh Gupta H Malathi Maharishi University of Information Technology Uttar Pradesh India Department of Management Sanskriti University Mathura Uttar Pradesh India Department of Biotechnology and Genetics School of Sciences JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

the usage of cognitive radios has enabled dynamic spectrum to get the right of entry to spectrum-congested regions. It has revolutionized how spectrum is allotted with the aid of turning the conventional static spectrum allocation into a dynamic and opportunistic method. Gadget studying-based totally spectrum sensing techniques have been advanced to permit optimized spectrum usage with better accuracy in cognitive radio networks. Those strategies use machine learning algorithms to learn the behaviors of spectrum assets and adaptively replace sensing strategies by intelligently deciding on the maximum suitable spectrum. This manner permits faster and more correct sensing in comparison to traditional spectrum sensing strategies. Furthermore, various fashions were proposed for specific spectrum sensing functionalities together with signal category, spectrum prediction, and function extraction. Those fashions are employed that allow you to maximize the spectrum assets utilization in cognitive radio networks. Furthermore, diverse processes have been proposed with the purpose of improving the overall performance of spectrum sensing techniques. Those consist of the usage of deep mastering fashions, exploiting heterogeneous facts sources, and using ensemble getting-to-know strategies. These approaches remember the complexity of the environment and permit extra correct and reliable choices. To conclude, device learning-based spectrum sensing techniques preserve a fantastic capacity for optimized spectrum utilization in cognitive radio networks. Consequently, they constitute a vital step forward closer to the improvement of green and reliable verbal exchange structures.

关键词： Performance evaluation Accuracy Noise signal processing algorithms Turning Sensors Complexity theory Cognitive radio Reliability Resource management

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Bio-signal Acquisition System for Psychological Stress Classification

Bio-Signal Acquisition System for Psychological Stress Class...

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International conference on Information and Communication Technology Convergence (ICTC)

作者： Daris Muhammad Rahman Arvanida Feizal Permana Maria Mahardini Sakanti Cornelia Adristi Win-Jet Luo C. Bambang Dwi Kuncoro Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan Graduate Institute of Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taiwan Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Depok Indonesia

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

The increasing prevalence of psychological stress in modern society necessitates the development of effective monitoring and classification systems. This paper presents the design and implementation of the acquisition system for the bio-signal measurement. The proposed system utilizes a combination of sensors and a microcontroller to collect and analyze physiological data indicative of stress levels. The bio-signals data monitored include heart rate, pulse rate, galvanic skin response, body temperature, and acceleration. The data acquisition process is managed by a microcontroller, which processes the raw signals and transmits them to a central processing unit for further analysis. The built system captures the acquired data in real time, offering immediate feedback and long-term monitoring capabilities. The system operates on a small power supply of 5V and 250mA, featuring a modular and portable design for ease of use. This approach aims to offer a cost-effective, non-invasive solution for early detection and management of psychological stress, contributing to improved mental health outcomes. Experimental results demonstrate the system's accuracy and reliability in acquiring and processing bio-signal data. These results represent preliminary research, with future work focusing on integrating advanced data analysis techniques and machine learning algorithms to enhance stress classification and prediction, expanding the system's applicability in clinical and everyday settings.

关键词： Temperature measurement Temperature sensors Heart rate Data analysis Power supplies Microcontrollers Human factors Skin Biomedical monitoring Monitoring

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Implementation of high speed data transfer serialized 128/130bit encoding algorithm using 90nm technology

Implementation of high speed data transfer serialized 128/13...

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International conference on advanced Computing and Communication Systems (ICACCS)

作者： F. Mhaboobkhan M. Fathimaparveen K. Gokila P. Logapriya Department of Electronics and Communication Engineering P.A College of Engineering and Technology Coimbatore

In the world of big data there has been a steady shift from parallel to high speed serial digital communication buses which requires devices with much higher data throughput. Serializing the data and sending at a faster rate, reduces the pin counts which in turn lead to much smaller devices in an integrated circuit compared to parallel communication. Line coding can potentially help in high data transfers. In this paper 128b/130b line coding algorithm has been proposed which has the double the payload of conventional 64b/66b encoding technique, with same number of preamble bits. This increases the data transfer rate drastically. The polynomial for the scrambler has been used from IEEE clause. The proposed 128b/130b encoding algorithm has been coded using Verilog and simulated using Quartus II 9.0v .The parameters such as Setup time, Hold time, Maximum frequency, power and slack for 8b/10b, 64b/66b and 128b/130b has been compared and tabulated. The layout has been designed for 128b/130b using Cadence Encounter 14.26 tool. The comparison shows that proposed algorithm has higher data rate at the expense of increase in hardware utilization.

关键词： Encoding Registers Timing Payloads signal processing algorithms Digital communication

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Nonnegative matrix factorization common spatial pattern in brain machine interface

Nonnegative matrix factorization common spatial pattern in b...

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International Winter Workshop on Brain-Computer Interface (BCI)

作者： H. Tsubakida T. Shiratori A. Ishiyama Y. Ono Graduate School of Advanced Science and Engineering Waseda Univ. Tokyo Japan Waseda Daigaku Shinjuku-ku Tokyo JP School of Science and Technology Meiji Univ. Kanagawa Japan

Fast and accurate discrimination of Electroencephalography (EEG) data is necessary for controlling brain machine interface. This paper introduces a novel method to discriminate 2-class motor imagery states (left and right hand) using nonnegative matrix factorization (NMF), common spatial pattern (CSP) and random forest. Conventionally CSP is used after extracting frequency band segment of EEG signal, which is called bandpass-filtered CSP (BPCSP). Especially filter bank CSP (FBCSP) has been extensively used to extract feature vectors from EEG data. However in these methods, the range of frequency band needed to be specified in advance and the performance depends on the selected frequency band. Our new method can decide the frequency band automatically by using NMF (NMFCSP). After the feature vectors were extracted from EEG data, random forests (RF) method was adopted as a classification algorithm. The mean accuracy rate of 2-class classifier using NMFCSP was 78.8±3.27%. This is higher than the accuracy rate of BPCSP (64.4±8.53%) and FBCSP (68.4±6.81%).

关键词： Electroencephalography Vectors Feature extraction Accuracy Matrix decomposition signal processing algorithms Continuous wavelet transforms

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