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2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)最新文献

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A 2x-Thru Standard De-embedding Method of Surface Components in High-Speed PCBs 高速pcb中表面元件的2 -通径标准脱嵌方法
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887402
Jian-Yao Ye, Jun Fan, Xin Cao, Qiangming Cai, Yuyu Zhu, Yuying Zhu
{"title":"A 2x-Thru Standard De-embedding Method of Surface Components in High-Speed PCBs","authors":"Jian-Yao Ye, Jun Fan, Xin Cao, Qiangming Cai, Yuyu Zhu, Yuying Zhu","doi":"10.23919/USNC-URSI52669.2022.9887402","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887402","url":null,"abstract":"This paper proposes a 2x-thru standard deembedding method for surface components in high-speed PCBs. This method uses one single symmetric fixture to de-embed device under tests (DUT) by extracting from the 2x-thru deembedding model in time domain channel characteristic analysis (TCC). The feasibility and accuracy of the method are verified using data obtained from simulated models with HFSS, and the de-embedding process is achieved with Matlab. The proposed method is compared with conventional Thru-reflect-line (TRL) method, and high precision has been proved. It requires far less standard fixtures and is much easier to implement. The proposed 2x-thru standard de-embedding method can be applied in high-speed circuits and on-chip components.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126570598","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
Combination of complex-valued neural networks with silicon-loaded probes for millimeter-wave non-invasive blood glucose concentration estimation 复合值神经网络与载硅探针结合用于毫米波无创血糖浓度估计
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887445
Seko Nagae, Lena Azuma, R. Natsuaki, A. Hirose
{"title":"Combination of complex-valued neural networks with silicon-loaded probes for millimeter-wave non-invasive blood glucose concentration estimation","authors":"Seko Nagae, Lena Azuma, R. Natsuaki, A. Hirose","doi":"10.23919/USNC-URSI52669.2022.9887445","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887445","url":null,"abstract":"This paper proposes a millimeter-wave human glucose-concentration estimation system based on the combination of a complex-valued neural network (CVNN) and dielectric-loaded probes. The system observes the complex-valued scattering coefficients in the millimeter-wave transmission through a thin human tissue such as an earlobe and a finger web, and estimates the concentration value by utilizing the CVNN learning ability. In this paper, we demonstrate that the silicon loading at the probes enhances the CVNN ability, resulting in a better estimation in in vivo experiments. The results will lead to the realization of reliable and practical non-invasive human blood glucose monitoring systems in the near future.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116641632","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: 1
EM Simulation of Sea Surface Point-to-Point Communication System 海面点对点通信系统的电磁仿真
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887448
Jiangnan Xing, Linshu Gong, Bin Cao, Tao Jiang
{"title":"EM Simulation of Sea Surface Point-to-Point Communication System","authors":"Jiangnan Xing, Linshu Gong, Bin Cao, Tao Jiang","doi":"10.23919/USNC-URSI52669.2022.9887448","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887448","url":null,"abstract":"According to the requirements of maritime emergency communication system, this paper proposed one solution of designing a portable communication device. First, the Pierson- Moscowitz ocean wave spectrum and creamer nonlinear surface generation method are used to build the geometric model of the sea surface. Second, it is calculated that the electromagnetic scattering characteristics of the sea surface, which deduced the model parameters of wireless channel on the sea surface. Finally, Third, he validation test of maritime emergency wireless transceiver design is achieved based on the HackRF module and the software radio development toolkit, which verifies the effectiveness of the channel model and the technical indicators of the transceiver.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"499 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133663912","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: 2
A Novel Exponentially Increased Irregular Minkowski Fractal Antenna 一种新型指数递增不规则Minkowski分形天线
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887411
Chenyi Wang, Xin Cao, Weiping Li, Qiangming Cai, Yuyu Zhu
{"title":"A Novel Exponentially Increased Irregular Minkowski Fractal Antenna","authors":"Chenyi Wang, Xin Cao, Weiping Li, Qiangming Cai, Yuyu Zhu","doi":"10.23919/USNC-URSI52669.2022.9887411","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887411","url":null,"abstract":"In this paper, a novel exponentially increased Minkowski fractal antenna is proposed. The topology of the antenna first adopts the irregular Minkowski geometric fractal to reduce size and increase operating bands. Then, the shape is modified to the exponential envelope to improve the gain and radiation pattern. The proposed antenna can work in flexible bands with high antenna gain in multi-band communication systems.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133785463","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
Dielectric Property Retrieval with Open-Ended Coaxial Probe for Solid Materials 用开放式同轴探针检索固体材料的介电特性
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887510
Cemanur Aydinalp, Sulayman Joof, M. N. Akıncı, I. Akduman, T. Yilmaz
{"title":"Dielectric Property Retrieval with Open-Ended Coaxial Probe for Solid Materials","authors":"Cemanur Aydinalp, Sulayman Joof, M. N. Akıncı, I. Akduman, T. Yilmaz","doi":"10.23919/USNC-URSI52669.2022.9887510","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887510","url":null,"abstract":"Determining the dielectric properties of materials based on their microwave features is an important research topic in various disciplines and industries. Accurate retrieval of solid material dielectric properties is one of the challenges in non-destructive measurement approaches. In this work, the dielectric property of three different flat-surface solid materials (kestamid, delrin and alumina) were retrieved from reflection coefficients through deep learning model from 0.5 to 6 GHz. The deep learning model was designed based on Debye parameters and reflection coefficients computed from the open-ended coaxial probe admittance model. The results were compared with commercially available Speag Dielectric Assessment Kit (DAK) software and the calculated percentage dielectric property differences are 5.5%, 6.8% and 7.5% for kestamid, delrin and alumina, respectively.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129332354","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
Two-dimensional Direction of Arrival Estimation based on Nested Circular Array 基于嵌套圆形阵列的二维到达方向估计
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887477
Bin Cao, Cong Xiong, Linshu Gong, T. Jiang
{"title":"Two-dimensional Direction of Arrival Estimation based on Nested Circular Array","authors":"Bin Cao, Cong Xiong, Linshu Gong, T. Jiang","doi":"10.23919/USNC-URSI52669.2022.9887477","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887477","url":null,"abstract":"Circular array is a widely used omnidirectional scanning array. Nested array is a new variant of circular array. However, the traditional direction of arrival is not effective in estimating the performance of the nested circular array. Therefore, this paper uses the differential common array domain method to analyze the two dimensional direction of arrival estimation performance of the sparse circular array. Simulation results show that the method adopted can effectively improve the direction of arrival estimation performance of nested circular arrays.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130569094","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: 1
Deep Neural Network for Localization of Mobile Users using Raytracing 基于光线追踪的移动用户定位深度神经网络
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887432
Jaspreet Kaur, O. Popoola, Muhammed Ali Imran, Q. Abbasi, H. Abbas
{"title":"Deep Neural Network for Localization of Mobile Users using Raytracing","authors":"Jaspreet Kaur, O. Popoola, Muhammed Ali Imran, Q. Abbasi, H. Abbas","doi":"10.23919/USNC-URSI52669.2022.9887432","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887432","url":null,"abstract":"As the world evolves towards faster data transmission, there is an ever-increasing demand for better user localization which will find application in transport, medicine, and robotics. In this study, we present an accurate localization algorithm for mobile users using deep neural network with Bayesian optimization and a communication channel operating at 3.75GHz frequency. We design a deep neural network model which facilitates and speeds up the localization process. The deep neural network (DNN) is utilized in this study to locate moving user equipment (UEs) with randomly assigned velocities. Using preliminary computer simulations, we present a method for training a neural network that extracts channel parameters (features) that are used to estimate location. Our method produces localization accuracy for line of sight (LOS) users, less than 1 m error, and the accuracy can further be improved by implementing higher rate of data sets.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"22 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120856647","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: 2
Energy-saving Algorithm of UAVs in Task Offloading of UAV-assisted Mobile Edge Computing 无人机辅助移动边缘计算任务卸载中的无人机节能算法
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887499
Jingchuan Zhang, Jingpeng Gao, Fang Ye, Yibing Li
{"title":"Energy-saving Algorithm of UAVs in Task Offloading of UAV-assisted Mobile Edge Computing","authors":"Jingchuan Zhang, Jingpeng Gao, Fang Ye, Yibing Li","doi":"10.23919/USNC-URSI52669.2022.9887499","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887499","url":null,"abstract":"UAV-assisted mobile edge computing (MEC) technology can expand the range of computing services and save the cost of base station deployment. However, the battery of the UAV is limited to provide continuous service. This paper studies the task offloading problem in UAV-assisted MEC and propose a matching game algorithm with bilateral preference lists. In this method, the user utility is modeled as the weighted sum of delay and energy consumption, and the UAV node preference is set as the sum of hovering and computing energy consumption. The experimental results show that the proposed algorithm can effectively reduce the computational energy consumption of UAV and trade off the user utility and UAV energy consumption.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131507765","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: 2
Design and Particle-In-Cell Modeling of Solid-State Travelling Wave Amplifier at 330 GHz 330ghz固态行波放大器的设计与细胞内粒子建模
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887453
Michail O. Anastasiadis, J. Volakis, S. Bhardwaj
{"title":"Design and Particle-In-Cell Modeling of Solid-State Travelling Wave Amplifier at 330 GHz","authors":"Michail O. Anastasiadis, J. Volakis, S. Bhardwaj","doi":"10.23919/USNC-URSI52669.2022.9887453","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887453","url":null,"abstract":"A novel implementation of a sub-THz travelling wave solid-state amplifier is presented. The proposed amplifier utilizes an interdigitated slow-wave structure in conjunction with a two-dimensional electron gas formed in a GaN/AlGaN heterostructure to amplify the input THz wave. The device is designed for operation at 330 GHz and Particle-In-Cell (PIC) simulations are used to evaluate the beam-wave interactions. An impressive gain of 23 dB is demonstrated.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132014540","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: 1
An Enhanced GPR FWI Scheme with Low-Frequency Data Extrapolated by Progressive Transfer Learning 基于渐进式迁移学习的低频数据外推增强GPR FWI方案
2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium) Pub Date : 2022-07-10 DOI: 10.23919/USNC-URSI52669.2022.9887483
Yuchen Jin, Yuan Zi, Xuqing Wu, Jiefu Chen
{"title":"An Enhanced GPR FWI Scheme with Low-Frequency Data Extrapolated by Progressive Transfer Learning","authors":"Yuchen Jin, Yuan Zi, Xuqing Wu, Jiefu Chen","doi":"10.23919/USNC-URSI52669.2022.9887483","DOIUrl":"https://doi.org/10.23919/USNC-URSI52669.2022.9887483","url":null,"abstract":"The ground penetrating radar (GPR) is an important technique for subsurface detection. The details of the geological model could be reconstructed by full waveform inversion (FWI) based on GPR data. Due to the device limitation, the low-frequency components are absent in the observations. These low-frequency components help GPR FWI avoid local minima. To extrapolate the low-frequency information from the band-limited observations, we propose a robust progressive transfer learning method. Benefiting from the combination between the physics-driven GPR FWI and the deep learning approach, our method shows a stronger generalization ability. We validate our method with synthetic data. Experiment results show that our method achieves fast convergence speed and high accuracy when the size of the training set is limited. The subsurface details are successfully reconstructed with extrapolated low-frequency data.","PeriodicalId":104242,"journal":{"name":"2022 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123177962","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
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