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Volume Integral Equations Combined with Orthogonality of Modes for Analysis of Two-Dimensional Optical Slab Waveguide 结合模正交性的体积积分方程分析二维平板光波导
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021rep0002
Masahiro Tanaka
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引用次数: 0
X-Band GaN Chipsets for Cost-Effective 20W T/R Modules 用于低成本20W T/R模块的x波段GaN芯片组
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021ecp5024
J. Kamioka, Yoshifumi Kawamura, Ryota Komaru, M. Hangai, Y. Kamo, Tetsuo Kodera, S. Shinjo
SUMMARY This paper reports on X-band Gallium Nitride (GaN) chipsets for cost-e ff ective 20W transmit-receive (T / R) modules. The chipset components include a GaN-on-Si monolithic microwave integrated circuit (MMIC) driver amplifier (DA), a GaN-on-SiC high power ampli-fier (HPA) with GaAs matching circuits, a high-gain GaN-on-Si HPA with a GaAs output matching circuit, and a GaN-on-Si MMIC switch (SW). By utilizing either combination of the DA or single high-gain HPA, the configurations of two T / R module types can be realized. The GaN-on-Si MMIC DA demonstrates an output power of 6.4–7.4W, an associate gain of 22.3–24.6dB and a power added e ffi ciency (PAE) of 32–36% over 9.0– 11.0GHz. A GaN-on-SiC HPA with GaAs matching circuits exhibited an output power of 20–28W, associate gain of 7.8–10.7dB, and a PAE of 40– 56% over 9.0–11.0GHz. The high-gain GaN-on-Si HPA with a GaAs output matching circuit exhibits an output power of 15–30W, associate gain of 27–30dB, and PAE of 26–33% over 9.0–11.0GHz. The GaN-on-Si MMIC switch demonstrates insertion losses of 1.1–1.3dB and isolation of 10.1– 14.7dB over 8.0–11.5GHz. By employing cost-e ff ective circuit configu-rations, the costs of these chipsets are estimated to be about half that of conventional chipsets
本文报道了用于低成本20W收发模块的x波段氮化镓(GaN)芯片组。芯片组组件包括GaN-on-Si单片微波集成电路(MMIC)驱动放大器(DA)、带有GaAs匹配电路的GaN-on-SiC高功率放大器(HPA)、带有GaAs输出匹配电路的高增益GaN-on-Si HPA和GaN-on-Si MMIC开关(SW)。通过使用数模组或单个高增益HPA的组合,可以实现两种收发模块类型的配置。GaN-on-Si MMIC DA的输出功率为6.4-7.4W,相关增益为22.3-24.6dB,功率增加效率(PAE)在9.0 - 11.0GHz范围内为32-36%。采用GaAs匹配电路的GaN-on-SiC HPA输出功率为20-28W,相关增益为7.8-10.7dB,在9.0-11.0GHz范围内的PAE为40 - 56%。具有GaAs输出匹配电路的高增益GaN-on-Si HPA输出功率为15-30W,相关增益为27-30dB,在9.0-11.0GHz范围内PAE为26-33%。GaN-on-Si MMIC开关在8.0-11.5GHz范围内的插入损耗为1.1-1.3dB,隔离度为10.1 - 14.7dB。通过采用具有成本效益的电路配置,这些芯片组的成本估计约为传统芯片组的一半
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引用次数: 0
A Review of GaN MMIC Power Amplifier Technologies for Millimeter-Wave Applications 毫米波应用GaN MMIC功率放大器技术综述
Pub Date : 2022-01-01 DOI: 10.1587/transele.2022mmi0006
K. Nakatani, Y. Yamaguchi, Takuma Torii, M. Tsuru
SUMMARY GaN microwave monolithic integrated circuit (MMIC) power amplifiers (PAs) technologies for millimeter-wave (mm-wave) applications are reviewed in this paper. In the mm-wave band, GaN PAs have achieved high-output power as much as traveling wave tube amplifiers used in satellite communications. Additionally, GaN PAs have been integrated enough to be used for 5G and Beyond-5G. In this paper, a high accuracy large-signal GaN-HEMT modeling technique including the trapping e ff ects is introduced in mm-waves. The prototyped PAs designed with the novel modeling technique have achieved RF performance comparable to that of the state-of-the-art GaN PAs in mm-wave.
综述了用于毫米波(mm-wave)的GaN微波单片集成电路(MMIC)功率放大器技术。在毫米波波段,GaN PAs已经实现了与卫星通信中使用的行波管放大器一样高的输出功率。此外,GaN PAs已经集成到足以用于5G和超5G。本文介绍了一种包含毫米波捕获效应的高精度大信号GaN-HEMT建模技术。采用新型建模技术设计的原型放大器在毫米波中实现了与最先进的GaN放大器相当的射频性能。
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引用次数: 4
SRAM: A Septum-Type Polarizer Design Method Based on Superposed Even- and Odd-Mode Excitation Analysis SRAM:一种基于奇偶模叠加激励分析的隔膜型偏振片设计方法
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021ecp5012
Tomoki Kaneko, H. Saito, A. Hirose
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引用次数: 2
A Discussion on Physical Optics Approximation for Edge Diffraction by A Conducting Wedge 关于导楔边缘衍射的物理光学近似的讨论
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021ecp5031
Duc Minh Nguyen, H. Shirai
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引用次数: 0
Deep-Learning-Assisted Single-Pixel Imaging for Gesture Recognition in Consideration of Privacy 考虑隐私的深度学习辅助单像素手势识别
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021dii0002
Naoya Mukojima, Masaki Yasugi, Y. Mizutani, T. Yasui, Hirotsugu Yamamoto
SUMMARY We have utilized single-pixel imaging and deep-learning to solve the privacy-preserving problem in gesture recognition for interactive display. Silhouette images of hand gestures were acquired by use of a display panel as an illumination. Reconstructions of gesture images have been performed by numerical experiments on single-pixel imaging by changing the number of illumination mask patterns. For the training and the image restoration with deep learning, we prepared reconstructed data with 250 and 500 illuminations as datasets. For each of the 250 and 500 illuminations, we prepared 9000 datasets in which original images and reconstructed data were paired. Of these data, 8500 data were used for training a neural network (6800 data for training and 1700 data for validation), and 500 data were used to evaluate the accuracy of image restoration. Our neural network, based on U-net, was able to restore images close to the original images even from reconstructed data with greatly reduced number of illuminations, which is 1/40 of the single-pixel imaging without deep learning. Compared restoration accuracy between cases using shadowgraph (black on white background) and negative-positive reversed images (white on black background) as silhouette image, the accuracy of the restored image was lower for negative-positive-reversed images when the number of illuminations was small. Moreover, we found that the restoration accuracy decreased in the order of rock, scissor, and paper. Shadowgraph is suitable for gesture silhouette, and it is necessary to prepare training data and construct neural networks, to avoid the restoration accuracy between gestures when further reducing the number of illuminations.
我们利用单像素成像和深度学习来解决交互式显示手势识别中的隐私保护问题。手势的轮廓图像是通过使用显示面板作为照明来获得的。通过改变照明掩模模式的数目,在单像素成像上进行了手势图像的重建实验。为了训练和深度学习图像恢复,我们准备了250和500照度的重建数据作为数据集。对于250和500照明中的每一个,我们准备了9000个数据集,其中原始图像和重建数据配对。其中8500个数据用于训练神经网络(6800个数据用于训练,1700个数据用于验证),500个数据用于评估图像恢复的准确性。我们基于U-net的神经网络,即使在光照数量大大减少的情况下,也能从重建的数据中恢复接近原始图像的图像,这是没有深度学习的单像素成像的1/40。对比阴影图(白色背景上的黑色)和正负反转图(黑色背景上的白色)作为剪影图像的恢复精度,光照数较少时正负反转图像的恢复精度较低。此外,我们发现恢复精度依次为岩石、剪刀和纸。阴影图适合于手势剪影,需要准备训练数据和构建神经网络,以避免在进一步减少光照数量时手势之间的恢复精度降低。
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引用次数: 2
Analysis of Efficiency-Limiting Factors Resulting from Transistor Current Source on Class-F and Inverse Class-F Power Amplifiers f类和反f类功率放大器晶体管电流源限制效率的因素分析
Pub Date : 2022-01-01 DOI: 10.1587/transele.2022mmi0003
H. Yamamoto, K. Kikuchi, V. Vadalà, G. Bosi, A. Raffo, G. Vannini
SUMMARY This paper describes the efficiency-limiting factors resulting from transistor current source in the case of class-F and inverse class-F (F -1 ) operations under saturated region. We investigated the influence of knee voltage and gate-voltage clipping behaviors on drain efficiency as limiting factors for the current source. Numerical analysis using a simplified transistor model was carried out. As a result, we have demonstrated that the limiting factor for class-F -1 operation is the gate-diode conduction rather than knee voltage. On the other hand, class-F PA is restricted by the knee voltage effects. Furthermore, nonlinear measurements carried out on a GaN HEMT validate our analytical results.
本文描述了在饱和区F类和反F类(F -1)操作的情况下,晶体管电流源产生的效率限制因素。作为电流源的限制因素,我们研究了膝电压和门电压截断行为对漏极效率的影响。采用简化的晶体管模型进行了数值分析。因此,我们已经证明了f -1类操作的限制因素是门二极管导通而不是膝电压。另一方面,f类PA受到膝关节电压效应的限制。此外,在GaN HEMT上进行的非线性测量验证了我们的分析结果。
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引用次数: 3
28nm Atom-Switch FPGA: Static Timing Analysis and Evaluation 28nm原子开关FPGA:静态时序分析与评估
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021fus0005
X. Bai, R. Nebashi, M. Miyamura, Kazunori Funahashi, N. Banno, K. Okamoto, Hideaki Numata, N. Iguchi, T. Sugibayashi, T. Sakamoto, M. Tada
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引用次数: 0
A Self-Powered Flyback Pulse Resonant Circuit for Combined Piezoelectric and Thermoelectric Energy Harvesting 一种用于压电和热电联合能量收集的自供电反激脉冲谐振电路
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021ecp5003
Huakang Xia, Yidie Ye, Xiudeng Wang, Ge Shi, Zhidong Chen, Libo Qian, Yinshui Xia
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引用次数: 0
Sputtering Gas Pressure Dependence on the LaBxNy Insulator Formation for Pentacene-Based Back-Gate Type Floating-Gate Memory with an Amorphous Rubrene Passivation Layer 溅射气体压力对具有非晶Rubrene钝化层的五苯基背栅式浮栅存储器LaBxNy绝缘体形成的影响
Pub Date : 2022-01-01 DOI: 10.1587/transele.2021fup0005
E. Hong, K. Park, S. Ohmi
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引用次数: 0
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IEICE Trans. Electron.
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