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Dual-Band Circularly Polarized Shared-aperture Vivaldi MIMO Antenna with Linear to Circular Polarizer for 5G and 6G Communication

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IEEE Transactions on Antennas and Propagation 2025年

作者： Wang, Ruiqi Ikram, Muhammad Yu, Yiyang Zhang, Haoran Shamim, Atif Computer Electrical and Mathematical Sciences and Engineering Division Thuwal23955 Saudi Arabia Kuwait

The upcoming sixth-generation (6G) communication system is set to operate in the Sub-THz band, which could provide substantially higher communication capacity. Meanwhile, the fifth-generation (5G) systems have already started to operate in the millimeter-wave (mm-Wave) bands. Therefore, dual-band antennas, which can operate for both 5G and 6G bands simultaneously, with circularly polarized (CP) radiation, are attractive for future wireless communication. However, achieving dual-band CP radiations, at frequencies as high as 100 GHz, is quite challenging. In this work, a novel dual-band, CP, eight-port multiple-input multiple-output (MIMO) antenna is presented. The proposed CP MIMO configuration comprises of orthogonally placed 4-element shared-aperture Vivaldi antenna and a linear-to-dual-circular polarization (LDCP) converter, operating at the frequencies of 40 GHz (5G mm-Wave band) and 110 GHz (6G sub-THz band). The shared-aperture Vivaldi antenna, proposed as the excitation source for the LDCP converter, demonstrates high gain, compact size, and end-fire linear polarization (LP) radiation for dual-wideband operation (5G/6G). The designed dual-band LDCP converter has a compact unit cell size (0.16λ at 40 GHz) and works for both horizontal and vertical polarizations. The fabricated prototype demonstrates a measured LHCP bandwidth from 39 to 45 GHz (14.2%) for the 5G band, and an RHCP bandwidth from 98 to 110 GHz (11.5%) for the 6G band. For the first time, we demonstrate a dual-band, dual-CP eight-port MIMO antenna with polarization (LHCP/RHCP) and spatial (30° incidence angle difference) diversity at the 5G/6G bands, making it a suitable candidate for future integrated 5G/6G communication systems. © 1963-2012 IEEE.

关键词： Millimeter waves

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Development of Vehicle-to-Grid Systemto Regulate the System Parameters of Microgrid

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Energy engineering 2022年第4期119卷 1261-1298页

作者： Om PrakashMahela Baseem Khan Rupendra Kumar Pachauri Power System Planning Division Rajasthan Rajya Vidyut Prasaran NigamLtd.Vidyut BhawanJapurIndia Department of Electrical and Computer Engineering Hawassa UniversityHawassaEthiopia Electrical Engineering Department School of EngineeringUniversity of Petroleum and Energy StudiesDehradunIndia

This paper proposes a vehicle-to-grid(V2G)system interfaced with a microgrid that is effective at regulating frequency on a microgrid over a 24-h cycle.A microgrid is designed and divided into four *** first component is a diesel generator,which is used to act as the base power *** second component consists of renewable energy(RE)power plants,which include solar photovoltaic(PV)and wind *** third component is a V2G *** last component is the load connected to the microgrid.A microgrid is designed to be of sufficient size to represent a community of one thousand households during the day period of low consumption in the spring or fall seasons.A hundred electric vehicles(EVs)are modeled as base models to realize a 1:10 ratio for cars to households,which indicates a possible scenario in the near *** analysis of the active power,reactive power,voltage,frequency,and current is carried *** is established that the proposed design of the V2G andmicrogrid effectivelymaintains systemparameters such as frequency and voltage within permissible limits with an error of less than 1%.Further,transient deviations in these parameters are limited to within 5%.A microgrid with V2G devices regulates the system frequency by mitigating load demand through coordinated control of conventional generation,solar PV plant generation,wind plant generation,power exchange with the microgrid network,and electric *** proposed microgrid and V2G are efficient for energy management and mitigation of intermittency and variability of RE power with improved *** in system parameters have been investigated by changing the operating scenario,and it has been determined that the error is limited to less than 5%.The study is effectively realized in the MATLAB/Simulink environment.

关键词： Microgrid electric vehicles vehicle-to-grid renewable energy PV wind

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Fully Inkjet-Printed Soft Wearable Strain Sensors Based on Metal/Polymer Composite Sensing Films 5

Fully Inkjet-Printed Soft Wearable Strain Sensors Based on M...

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5th IEEE International Conference on Flexible and Printable Sensors and Systems, FLEPS 2023

作者： Khan, Arshad Ali, Shawkat Nittala, Aditya Shekhar Riaz, Kashif Bermak, Amine College of Science and Engineering Hamad Bin Khalifa University Division of Information and Computing Technology Doha Qatar Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia University of Calgary Department of Computer Science Calgary Canada

ISBN: (纸本)9781665457330

In this paper, we present a high-performance soft strain sensor that uses composite sensing layers made of metal and polymer. This strain sensor is entirely developed by inkjet-printing the composite films on a highly stretchable thermoplastic polyurethane (TPU) substrate and a textile-compatible polymer film, which makes the process easy, affordable, energy-efficient, and scalable. The sensing patches are made up of two films: a PEDOT:PSS-based conductive polymer top film and a metal bottom film composed of silver nanoparticles. The sensor has a decent sensing range (≈10% strain), high sensitivity (GF ≈ 12), and outstanding mechanical stability (>1000 cycles), making it suitable for both stretching and bending deformation detection. As application examples, the soft sensors are used to track the highly deformed human body motions, displaying excellent performance. The outcomes demonstrate the attractiveness and potential of our low-cost soft strain sensors for real-world uses, such as the wide-range tracking of human movements. © 2023 IEEE.

关键词： Polymer films

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Super-LoRa: Enhancing LoRa Throughput via Payload Superposition

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IEEE Internet of Things Journal 2025年

作者： Abdeljabar, Salah Alouini, Mohamed-Slim Computer Electrical and Mathematical Science and Engineering Division Thuwal 23955-6900 Saudi Arabia

This paper presents Super-LoRa, a novel approach to enhancing the throughput of LoRa networks by leveraging the inherent robustness of LoRa modulation against interference. By superimposing multiple payload symbols, Super-LoRa significantly increases the data rate while maintaining lower transmitter and receiver complexity. Our solution is evaluated through both simulations and real-world experiments, showing a potential throughput improvement of up to 5× compared to standard LoRa. This advancement positions Super-LoRa as a viable solution for data-intensive IoT applications such as smart cities and precision agriculture, which demand higher data transmission rates. © 2014 IEEE.

关键词： Sugar cane

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Vision-Based Fixed-Time Uncooperative Aerial Target Tracking for UAV

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1322-1324页

作者： Peng Sun Siqi Li Bing Zhu Zongyu Zuo Xiaohua Xia the Seventh Research Division Beihang UniversityBeijing 100191China the School of Automation Beijing Institute of TechnologyBeijing 100081China the Department of Electrical Electronic and Computer EngineeringUniversity of PretoriaPretoria 0002South Africa

Dear Editor,In this letter,a vision-based fixed-time control is proposed for an unmanned aerial vehicle(UAV)with actuator saturation to track an uncooperative *** fixed-time control is designed in backstepping *** rel... 详细信息

关键词： Fixed cooperative letter

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The Costly Effect of Poor Power Factor on an Electric Utility Bill

The Costly Effect of Poor Power Factor on an Electric Utilit...

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2023 IEEE International Conference on electrical, computer and Energy Technologies, ICECET 2023

作者： Creeden, Evan A.M. Yang, Fang Eaton Corporation Eaton Electrical Services and Systems Division Chicago United States University of Wisconsin-Platteville Department of Electrical and Computer Engineering Platteville United States

ISBN: (纸本)9798350327816

Much of the industrialized world contains significant motor loads which can greatly increase the reactive power demand of any power system. Which increases the overall demand as well. This forces power utility companies to produce more energy to meet this demand than if the system were running more efficiently. Measuring reactive power with typical utility meters and directly billing for reactive power is difficult and ambiguous. Moreover, having to produce and supply reactive power is costly and inefficient for the utility company. As such, each utility has their own internal or region-wide rules/tariffs for recouping this cost from their customers. Looking at the United States, given the many different state laws and utility companies, it is not feasible to have a standard method for billing customers for their reactive power consumption. Therefore, it is left to state legislature and the policies of the power utility companies. In addition to this lack of standard, the lack of understanding surrounding power factor leaves many customers, who own/operate industrial plants with large motor loads, confused and with rather expensive monthly electric bills. This paper intends to investigate the general billing of power and energy from a utility, and especially the many ways to bill reactive power. This study also features an analysis and comparison of how the United States' top five power utility companies define and charge industrial plants for reactive power. © 2023 IEEE.

关键词： Billing Power and Energy Power Factor Power Factor Correction Rates and Tariffs Reactive Power Utility Companies

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A machine learning-guided design and manufacturing of wearable nanofibrous acoustic energy harvesters

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Nano Research 2024年第10期17卷 9181-9192页

作者： Negar Hosseinzadeh Kouchehbaghi Maryam Yousefzadeh Aliakbar Gharehaghaji Safoora Khosravi Danial Khorsandi Reihaneh Haghniaz Ke Cao Mehmet R.Dokmeci Mohammad Rostami Ali Khademhosseini Yangzhi Zhu Terasaki Institute for Biomedical Innovation Los AngelesCA 91367USA Department of Textile Engineering Amirkabir University of Technology(Tehran Polytechnic)Hafez Avenue*** TehranIran Department of Electrical and Computer Engineering University of British ColumbiaVancouverBC V6T1Z4Canada Chemical Sciences Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Department of Computer Science University of Southern CaliforniaLos AngelesCA 90007USA

Nanofibrous acoustic energy harvesters(NAEHs)have emerged as promising wearable platforms for efficient noise-to-electricity conversion in distributed power energy systems and wearable sound amplifiers for assistive listening ***,their reallife efficacy is hampered by low power output,particularly in the low-frequency range(<1 kHz).This study introduces a novel approach to enhance the performance of NAEHs by applying machine learning(ML)techniques to guide the synthesis of electrospun polyvinylidene fluoride(PVDF)/polyurethane(PU)nanofibers,optimizing their application in wearable *** use a feed-forward neural network along with solving an optimization problem to find the optimal input values of the electrospinning(applied voltage,nozzle-collector distance,electrospinning time,and drum rotation speed)to generate maximum output performance(acoustic-to-electricity conversion efficiency).We first prepared a dataset to train the network to predict the output power given the input variables with high *** introducing the neural network,we fix the network and then solve an optimization problem using a genetic algorithm to search for the input values that lead to the maximum energy harvesting *** ML-guided wearable PVDF/PU NAEH platform can deliver a maximal acoustoelectric power density output of 829μW/cm^(3) within the surrounding noise *** addition,our system can function stably in a broad frequency(0.1-2 kHz)with a high energy conversion efficiency of 66%.Sound recognition analysis reveals a robust correlation exceeding 0.85 among lexically akin terms with varying sound intensities,contrasting with a diminished correlation below 0.27 for words with disparate semantic ***,this work provides a previously unexplored route to utilize ML in advancing wearable NAEHs with excellent practicability.

关键词： wearable electronics acoustic energy harvester machine learning piezoelectric nanogenerator electrospun nanofiber

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Enhancing Power Quality through Harmonic Reduction: A Triple-Memristor Hopfield Neural Network Approach 8

Enhancing Power Quality through Harmonic Reduction: A Triple...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Varaprasad, K.S.B. Sukhi, Y. Subramaniyan, Shanmugapriya Dhandapani, Ramya Rajendiran, M. Kaliappan, S. Visakha Institute of Engineering & Technology Department of Electrical and Electronics Engineering Andhra Pradesh Visakhapatnam530027 India R.M.K. Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Tiruvallur601206 India Srm Institute of Science & Technology Department of Electrical and Electronics Engineering Tamil Nadu Kattankulathur603203 India Sri Eshwar College of Engineering Coimbatore Department of Computer Science and Business Systems Tamil Nadu Coimbatore641202 India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai600123 India Lovely Professional University Division of Research and Development Delhi Jalandhar144411 India

ISBN: (纸本)9798350376425

Harmonic distortion in power systems is a significant concern that impacts the efficiency, reliability, and safety of electrical networks. Implementing effective harmonic distortion mitigation solutions, such as filters or advanced control systems, can be expensive and may necessitate substantial changes to existing infrastructure. This paper proposes a Triple-Memristor Hopfield Neural Network (TMHNN) as a novel method for mitigating harmonic distortion in power systems. The main objective of the proposed approach is to improve the quality of power by mitigating the harmonics. The TMHNN is used to predict the actual harmonic current injected by specific harmonic sources within a power system. The results demonstrate the significant advantages of the proposed TMHNN method over existing techniques such as Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Recurrent Neural Network (RNN). TMHNN achieves the highest efficiency at 96.3%, lowest error rate at 4.16% and minimizing total harmonic distortion (THD), with the lowest value of 3.74%. These results highlight TMHNN's superior performance in terms of efficiency, harmonic distortion reduction, and accuracy. © 2024 IEEE.

关键词： Harmonic distortion

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In situ and operando infrared spectroscopy of battery systems:Progress and opportunities

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Journal of Energy Chemistry 2023年第6期81卷 472-491,I0011页

作者： Murilo M.Amaral Carla G.Real Victor Y.Yukuhiro Gustavo Doubek Pablo S.Fernandez Gurpreet Singh Hudson Zanin Advanced Energy Storage Division Center for Innovation on New EnergiesSchool of Electrical and Computer EngineeringUniversity of CampinasCampinasSP 13083-852Brazil Alan Levin Department of Mechanical and Nuclear Engineering Kansas State UniversityManhattanKS 66506USA Chemistry Institute Center for Innovation on New EnergiesUniversity of CampinasCampinasSP 13083-970Brazil Advanced Energy Storage Division Center for Innovation on New EnergiesSchool of Chemical EngineeringUniversity of CampinasCampinasSP 13083-852Brazil

In situ and operando infrared spectroscopies are powerful techniques to support the design of novel materials for batteries and the development of new battery *** techniques can support the study of batteries by identifying the formation of new species and monitoring electrochemical energy ***,few works have employed these techniques,which can be used to investigate various materials,including systems beyond lithium-ion technology,in the research of ***,this review presents a comprehensive overview focusing on the main contributions of in situ and operando infrared spectroscopy for lithium-ion batteries(LIBs)and other battery *** techniques can successfully identify the formation of species during the electrolyte reduction,electrode degradation,and the formation of the solid-electrolyte interphase(SEI)*** these outcomes,it is possible to conclude that this characterization approach should be employed as a protocol to overcome remaining issues in batteries,consequently supporting battery *** review aims to be a guide on how infrared spectroscopy can contribute to monitoring battery systems and to lead researchers interested in applying this technique.

关键词： In situ spectroscopy Operando spectroscopy FTIR Spectro-electrochemical cells Batteries

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Detection and Mitigation of Subtle Feature-map Attacks in Pseudo Parallel Collaborative CNN Models for Distributed Edge Intelligence 100

Detection and Mitigation of Subtle Feature-map Attacks in Ps...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Patel, Parth Hasan, Syed Rafay Rahman, Mohammad Ashiqur Homsi, Soamar Tennessee Tech University Department of Electrical and Computer Engineering United States Florida International University Department of Computer Science United States AirForce Research Laboratory Information Warfare Division United States

ISBN: (纸本)9798331517786

Although Collaborative Deep Neural Network (CDNN) promises to be an alternative mechanism to mitigate the effects of the untrusted cloud, this approach is susceptible to other kinds of adversarial attacks, which arise from one or more untrusted devices in CDNN acting maliciously. However, since each untrusted node in the CDNN contains only partial information of the complete DNN model, it is worth investigating whether the attacker can still muster a viable threat to CDNN or not. This led to the investigation of attack scenarios and their effects on convolutional neural networks (CNN) used for image classification in the CDNN environment. In this research, we are investigating the shortcomings of existing attacks on CDNN, that lead to non-subtle attack to the defender who is on look out against such attacks. Our research showed that sparse nature of feature maps (FMs) due to the ReLU function lead to many existing attacks more obvious to the attacker. Next, we investigated how one can detect the existing attacks if the defender has some previous knowledge of the complete CNN's FMs. Our results show minimal detection overhead of about 2%, with an accuracy of 95% and F1 score of above 0.97. © 2024 IEEE.

关键词： Convolutional neural networks

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