Progress in Electromagnetics Research M最新文献

Optimizing Detection in MIMO OFDM Radar: Methods for Eliminating Distance-angle Coupling in Beamforming MIMO OFDM雷达的优化检测:波束形成中消除距离角耦合的方法

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23080103

Doudou Huang, Yurong Wu, Mingliang Shen, Longshan Xu, Jun Tang

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Millimeter Wave Attenuation in the Coastal Area of the Gulf of Guinea Subject to Heavy Rainfalls 几内亚湾沿岸地区受大雨影响的毫米波衰减

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23071204

Benjamin Tanga Louk, Raphael Onguene, Serge Raoul Dzonde Naoussi, Sakaros Bogning, Jacques Etame, Modeste Kacou, Patrick Herve Ntanguen

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2-Port High Gain Millimeter-wave MIMO Antenna for 5G Applications 用于5G应用的2端口高增益毫米波MIMO天线

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23080707

Mingming Gao, Hongliang Niu, Jing Chang Nan, Wen Hui Liu, Chun Li Liu

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A Wideband High-gain Antenna Loaded with Triangular Ring Metasurface 一种加载三角环超表面的宽带高增益天线

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23082902

Ting Wu, Jia-Wei Wang, Mingjun Wang, Kai Zhang

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A Novel Passive Millimeter Wave Image Noise Suppression Method Based on Pixel Non-local Self-similarity 一种基于像素非局部自相似的毫米波图像无源噪声抑制方法

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23090702

Jin Yang, Yuehua Li

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Dual-band 4-port Vivaldi MIMO Antenna for 5G mmWave Applications at 28/39 GHz 用于5G毫米波应用的28/39 GHz双频4端口Vivaldi MIMO天线

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23080401

Golla Ramyasree, Nelaturi Suman

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Analytical Neuro-space Mapping Technology for Heterojunction Bipolar Transistors Modeling 异质结双极晶体管建模的分析神经空间映射技术

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23080706

Shuxia Yan, Yuxing Li, Chenglin Li, Fengqi Qian, Xu Wang, Wenyuan Liu

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A Quad-band Low Power High Sensitive RF to DC Converter Circuit for RF Energy Harvesting Applications 一种用于射频能量收集的四波段低功率高灵敏度射频到直流转换电路

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23073105

Pavan Mehta, Anveshkumar Nella

{"title":"A Quad-band Low Power High Sensitive RF to DC Converter Circuit for RF Energy Harvesting Applications","authors":"Pavan Mehta, Anveshkumar Nella","doi":"10.2528/pierm23073105","DOIUrl":"https://doi.org/10.2528/pierm23073105","url":null,"abstract":"|In recent years, Radio Frequency Energy Harvesting (RFEH) has matured into a trustworthy and consistent method of obtaining ambient energy. For this energy to be utilized, it must be collected as eﬃciently over a broad range of frequencies as possible. In this regard, this article introduces a quad-band low-power, highly sensitive Radio Frequency (RF) to Direct Current (DC) signal converter circuit that operates at 1.5 GHz, 2.45 GHz, 3.6 GHz, and 5.5 GHz bands. The converter circuit is realized through single and dual-band converter circuit studies. These circuits comprise an impedance matching circuit, a voltage-doubler recti(cid:12)er, a DC-pass (cid:12)lter with a resistive load of 5 kΩ, and a DC-DC voltage booster (LTC3108). The proposed quad-band converter circuit without a voltage booster gives a DC output voltage of 118 mV, 81 mV, 56 mV, and 24 mV at the four operational frequencies on a low input power of (cid:0) 25 dBm, respectively. A DC voltage of 3.3 V is obtained when the converter circuit is connected to a voltage booster. Maximum conversion eﬃciency achieved is 48% from four tones on a power input of (cid:0) 10 dBm. Circuit design steps, matching conditions, and performance parameters are presented using the Advanced Design System (ADS) and LTspice simulation tools.","PeriodicalId":39028,"journal":{"name":"Progress in Electromagnetics Research M","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136208265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Optimization of 2D Photonic Crystal Based Compact All Optical T Splitter for Photonic Integrated Circuits 光子集成电路中基于二维光子晶体的紧凑全光T分路器的设计与优化

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23080801

Poonam Jindal, Aarti Bansal

引用次数: 0

AI-based Fast Design for General Fiber-to-waveguide Grating Couplers 基于人工智能的通用光纤波导光栅耦合器快速设计

Progress in Electromagnetics Research M Pub Date : 2023-01-01 DOI: 10.2528/pierm23072703

Zhenjia Zeng, Qiangsheng Huang, Sailing He

{"title":"AI-based Fast Design for General Fiber-to-waveguide Grating Couplers","authors":"Zhenjia Zeng, Qiangsheng Huang, Sailing He","doi":"10.2528/pierm23072703","DOIUrl":"https://doi.org/10.2528/pierm23072703","url":null,"abstract":"|Utilizing deep learning to replace numerical simulation solvers for electromagnetic wave propagation is a promising approach for the rapid design of photonic devices. However, to realize the advantages of deep learning for rapid design, it is essential to apply it to a general device structure. In this study, we propose a method that employs deep learning to assist in fast design of a general grating coupler structure. We use a modi(cid:12)ed 1D-ResNet18(1D-MR18) to predict the coupling eﬃciency of various grating couplers at diﬀerent wavelengths. After comparing and selecting the optimal combination of learning rate, activation functions, and batch normalization size, the 1D-MR18 demonstrates remarkable accuracy ( MSE : 2 : 18 (cid:2) 10 (cid:0) 5 , R 2 : 0 : 969, MAE : 0 : 003). By integrating the 1D-MR18 with the adaptive particle swarm algorithm, we can eﬃciently design periodic and nonuniform grating couplers that meet various functional requirements, including single-wavelength grating couplers, multi-wavelength grating couplers, and robust grating couplers. The time for designing a single device is no more than 2 minutes, and the shortest is only 17 seconds. This novel approach of employing deep learning for the fast and eﬃcient design from standard photonic device structures oﬀers valuable insights and guidance for photonic devices design.","PeriodicalId":39028,"journal":{"name":"Progress in Electromagnetics Research M","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135954498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0