scholarly journals Linear Characterization and Modeling of GaN-on-Si HEMT Technologies with 100 nm and 60 nm Gate Lengths

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 134
Author(s):  
Sergio Colangeli ◽  
Walter Ciccognani ◽  
Patrick Ettore Longhi ◽  
Lorenzo Pace ◽  
Julien Poulain ◽  
...  
Keyword(s):  
Test Bench ◽  
Linear Models ◽  
Noise Figure ◽  
Low Cost ◽  
Noise Temperature ◽  
Equivalent Circuit Model ◽  
Nondestructive Method ◽  
Noise Model ◽  
Gate Length ◽  
Gan On Si

Motivated by the growing interest towards low-cost, restriction-free MMIC processes suitable for multi-function, possibly space-qualified applications, this contribution reports the extraction of reliable linear models for two advanced GaN-on-Si HEMT technologies, namely OMMIC’s D01GH (100 nm gate length) and D006GH (60 nm gate length). This objective is pursued by means of both classical and more novel approaches. In particular, the latter include a nondestructive method for determining the extrinsic resistances and an optimizaion-based approach to extracting the remaining parasitic elements: these support standard DC and RF measurements in order to obtain a scalable, bias-dependent equivalent-circuit model capturing the small-signal behavior of the two processes. As to the noise model, this is extracted by applying the well known noise-temperature approach to noise figure measurements performed in two different frequency ranges: a lower band, where a standard Y-factor test bench is used, and an upper band, where a custom cold-source test bench is set up and described in great detail. At 5 V drain-source voltage, minimum noise figures as low as 1.5 dB and 1.1 dB at 40 GHz have been extracted for the considered 100 nm and 60 nm HEMTs, respectively: this testifies the maturity of both processes and the effectiveness of the gate length reduction. The characterization and modeling campaign, here presented for the first time, has been repeatedly validated by published designs, a couple of which are reviewed for the Reader’s convenience.

scholarly journals Design and Validation of 100 nm GaN-On-Si Ka-Band LNA Based on Custom Noise and Small Signal Models

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 150 ◽  
Author(s):  
Lorenzo Pace ◽  
Sergio Colangeli ◽  
Walter Ciccognani ◽  
Patrick Ettore Longhi ◽  
Ernesto Limiti ◽  
...  
Keyword(s):  
Noise Figure ◽  
Low Noise ◽  
Low Noise Amplifier ◽  
Gate Length ◽  
Small Signal ◽  
Linear Measurements ◽  
Ka Band ◽  
Noise Amplifier ◽  
Gan On Si ◽  
Noise Models

In this paper a GaN-on-Si MMIC Low-Noise Amplifier (LNA) working in the Ka-band is shown. The chosen technology for the design is a 100 nm gate length HEMT provided by OMMIC foundry. Both small-signal and noise models had been previously extracted by the means of an extensive measurement campaign, and were then employed in the design of the presented LNA. The amplifier presents an average noise figure of 2.4 dB, a 30 dB average gain value, and input/output matching higher than 10 dB in the whole 34–37.5 Ghz design band, while non-linear measurements testify a minimum output 1 dB compression point of 23 dBm in the specific 35–36.5 GHz target band. This shows the suitability of the chosen technology for low-noise applications.

scholarly journals Microwave Analysis for Two-Dimensional C-V and Noise Model of AlGaN/GaN MODFET

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ramnish Kumar ◽  
Sandeep K. Arya ◽  
Anil Ahlawat
Keyword(s):  
Noise Figure ◽  
Noise Model ◽  
Gate Length ◽  
Two Dimensional ◽  
High Frequencies ◽  
Noise Characteristics ◽  
Proposed Model ◽  
Dimensional Electron Gas ◽  
High Transconductance ◽  
Gate Resistance

A new two-dimensional analytical model for the capacitance-voltage and noise characteristics of a AlGaN/GaN MODFET is developed. The two-dimensional electron gas density is calculated as a function of device dimensions. The model includes the spontaneous and polarization effects. The contribution of various capacitances to the performance of the device is shown. The model further predicts the transconductance, drain conductance, and frequency of operation. A high transconductance of 160 mS/mm and a cut-off frequency of 11.6 GHz are obtained for a device of 50 nm gate length. The effect of gate length on the gate length behaviour of the noise coefficientsP,R, andCis also studied. The effect of parasitic source and gate resistance has also been studied to evaluate the minimum noise figure. The excellent agreement with the previously simulated results confirms the validity of the proposed model to optimize the device performance at high frequencies.

scholarly journals Reconstruction of Relative Phase of Self-Transmitting Devices by Using Multiprobe Solutions and Non-Convex Optimization

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2459
Author(s):  
Rubén Tena Sánchez ◽  
Fernando Rodríguez Varela ◽  
Lars J. Foged ◽  
Manuel Sierra Castañer
Keyword(s):  
Iterative Algorithm ◽  
Degrees Of Freedom ◽  
Relative Phase ◽  
Low Cost ◽  
Initial Guess ◽  
Noise Model ◽  
Medium Size ◽  
Phase Reconstruction ◽  
Linear Combinations ◽  
Iterative Optimization Algorithm

Phase reconstruction is in general a non-trivial problem when it comes to devices where the reference is not accessible. A non-convex iterative optimization algorithm is proposed in this paper in order to reconstruct the phase in reference-less spherical multiprobe measurement systems based on a rotating arch of probes. The algorithm is based on the reconstruction of the phases of self-transmitting devices in multiprobe systems by taking advantage of the on-axis top probe of the arch. One of the limitations of the top probe solution is that when rotating the measurement system arch, the relative phase between probes is lost. This paper proposes a solution to this problem by developing an optimization iterative algorithm that uses partial knowledge of relative phase between probes. The iterative algorithm is based on linear combinations of signals when the relative phase is known. Phase substitution and modal filtering are implemented in order to avoid local minima and make the algorithm converge. Several noise-free examples are presented and the results of the iterative algorithm analyzed. The number of linear combinations used is far below the square of the degrees of freedom of the non-linear problem, which is compensated by a proper initial guess. With respect to noisy measurements, the top probe method will introduce uncertainties for different azimuth and elevation positions of the arch. This is modelled by considering the real noise model of a low-cost receiver and the results demonstrate the good accuracy of the method. Numerical results on antenna measurements are also presented. Due to the numerical complexity of the algorithm, it is limited to electrically small- or medium-size problems.

scholarly journals Robust Silent Localization of Underwater Acoustic Sensor Network Using Mobile Anchor(s)

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 727
Author(s):  
Rahul Mourya ◽  
Mauro Dragone ◽  
Yvan Petillot
Keyword(s):  
Channel Model ◽  
Low Cost ◽  
Sensor Nodes ◽  
Noise Model ◽  
Robust Estimator ◽  
Acoustic Sensor ◽  
Underwater Acoustic ◽  
Acoustic Channel ◽  
Localization Scheme ◽  
Mobile Anchor

Underwater acoustic sensor networks (UWASNs) can revolutionize the subsea domain by enabling low-cost monitoring of subsea assets and the marine environment. Accurate localization of the UWASNs is essential for these applications. In general, range-based localization techniques are preferred for their high accuracy in estimated locations. However, they can be severely affected by variable sound speed, multipath spreading, and other effects of the acoustic channel. In addition, an inefficient localization scheme can consume a significant amount of energy, reducing the effective life of the battery-powered sensor nodes. In this paper, we propose robust, efficient, and practically implementable localization schemes for static UWASNs. The proposed schemes are based on the Time-Difference-of-Arrival (TDoA) measurements and the nodes are localized passively, i.e., by just listening to beacon signals from multiple anchors, thus saving both the channel bandwidth and energy. The robustness in location estimates is achieved by considering an appropriate statistical noise model based on a plausible acoustic channel model and certain practical assumptions. To overcome the practical challenges of deploying and maintaining multiple permanent anchors for TDoA measurements, we propose practical schemes of using a single or multiple surface vehicles as virtual anchors. The robustness of localization is evaluated by simulations under realistic settings. By combining a mobile anchor(s) scheme with a robust estimator, this paper presents a complete package of efficient, robust, and practically usable localization schemes for low-cost UWASNs.

Mixed H2/H∞ Observer-Based LPV Control of a Hydraulic Engine Cam Phasing Actuator

2011 ◽  
Author(s):  
Andrew White ◽  
Zhen Ren ◽  
Guoming Zhu ◽  
Jongeun Choi
Keyword(s):  
Engine Speed ◽  
Test Bench ◽  
Linear Models ◽  
Linear Matrix ◽  
Closed Loop System ◽  
Linear Parameter Varying ◽  
The Family ◽  
Lpv Control ◽  
Lpv System ◽  
Variable Valve

In this paper, a series of closed-loop system identification tests was performed for a variable valve timing cam phaser system on a test bench to obtain a family of linear models for an array of engine speeds and oil pressures. Using engine speed and oil pressure as the system parameters, the family of linear models was translated into a linear parameter varying (LPV) system. The engine speed and oil pressure can be measured in real-time by these sensors equipped on the engine, thus allowing their use as scheduling parameters. An observer-based gain-scheduling controller for the obtained LPV system is then designed based on the numerically efficient convex optimization or linear matrix inequality (LMI) technique. Test bench results show the effectiveness of the proposed scheme.

scholarly journals Using decades of spawning data and hydraulic models to construct a temperature dependent resource selection function for management of an endangered salmonid

2021 ◽  
Author(s):  
Peter N Dudley ◽  
Sara N John ◽  
Miles E Daniels ◽  
Eric M. Danner
Keyword(s):  
Water Temperature ◽  
Environmental Variables ◽  
Resource Selection ◽  
Oncorhynchus Tshawytscha ◽  
Linear Models ◽  
Low Cost ◽  
Hydraulic Modeling ◽  
Selection Function ◽  
Spawning Habitat ◽  
Increasing Temperature

In North America, impassable, man-made barriers block access to salmonid spawning habitat and require costly restoration efforts in the remaining habitats. Evaluating restored spawning habitat quality requires information on salmon water velocity and depth preferences, which may vary in relation to other variables (e.g. water temperature). We demonstrate a generalizable, low cost method to gather and analyze this data by combining aerial redd surveys of winter-run Chinook salmon (Oncorhynchus tshawytscha), 2D hydraulic modeling, and generalized linear models to calculate spawning resource selection functions (RSFs). Our method permits the examination of interactions between environmental variables on habitat selection, which are frequently treated as independent. Our methods resulted in a RSF that shows interactions between both velocity and depth preference with changing temperature. Preferred depth increased and preferred velocity decreased with increasing temperature. Spawning RSFs for environmental variables may change as other environmental conditions (i.e. water temperature) change, thus it is importance to account for potential interactions when using or producing RSFs.

scholarly journals Wind Turbine Noise Reduction from Seismological Data

2021 ◽  
Author(s):  
Janis Heuel ◽  
Wolfgang Friederich
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Computational Cost ◽  
Noise Signal ◽  
Noise Model ◽  
Threshold Function ◽  
High Signal ◽  
Time Data ◽  
Negative Effects ◽  
Before And After

<p>Over the last years, installations of wind turbines (WTs) increased worldwide. Owing to<br>negative effects on humans, WTs are often installed in areas with low population density.<br>Because of low anthropogenic noise, these areas are also well suited for sites of<br>seismological stations. As a consequence, WTs are often installed in the same areas as<br>seismological stations. By comparing the noise in recorded data before and after<br>installation of WTs, seismologists noticed a substantial worsening of station quality leading<br>to conflicts between the operators of WTs and earthquake services.</p><p>In this study, we compare different techniques to reduce or eliminate the disturbing signal<br>from WTs at seismological stations. For this purpose, we selected a seismological station<br>that shows a significant correlation between the power spectral density and the hourly<br>windspeed measurements. Usually, spectral filtering is used to suppress noise in seismic<br>data processing. However, this approach is not effective when noise and signal have<br>overlapping frequency bands which is the case for WT noise. As a first method, we applied<br>the continuous wavelet transform (CWT) on our data to obtain a time-scale representation.<br>From this representation, we estimated a noise threshold function (Langston & Mousavi,<br>2019) either from noise before the theoretical P-arrival (pre-noise) or using a noise signal<br>from the past with similar ground velocity conditions at the surrounding WTs. Therefore, we<br>installed low cost seismometers at the surrounding WTs to find similar signals at each WT.<br>From these similar signals, we obtain a noise model at the seismological station, which is<br>used to estimate the threshold function. As a second method, we used a denoising<br>autoencoder (DAE) that learns mapping functions to distinguish between noise and signal<br>(Zhu et al., 2019).</p><p>In our tests, the threshold function performs well when the event is visible in the raw or<br>spectral filtered data, but it fails when WT noise dominates and the event is hidden. In<br>these cases, the DAE removes the WT noise from the data. However, the DAE must be<br>trained with typical noise samples and high signal-to-noise ratio events to distinguish<br>between signal and interfering noise. Using the threshold function and pre-noise can be<br>applied immediately on real-time data and has a low computational cost. Using a noise<br>model from our prerecorded database at the seismological station does not improve the<br>result and it is more time consuming to find similar ground velocity conditions at the<br>surrounding WTs.</p>

scholarly journals A linear model for leaf area measurement to screen potential leaf material for herbal drug in Adhatoda vasica L.

2016 ◽  
Vol 8 (1) ◽  
pp. 140-143
Author(s):  
J. V. Thaker ◽  
R. P. Kuvad ◽  
V. S. Thaker
Keyword(s):  
Water Content ◽  
Leaf Area ◽  
Linear Model ◽  
Plant Species ◽  
Linear Models ◽  
Dry Weight ◽  
Nondestructive Method ◽  
Area Measurement ◽  
Adhatoda Vasica ◽  
Linear Correlations

Leaf area is an important parameter in physiology and agronomy studies. Linear models for leaf area measurement are developed for plant species as a nondestructive method. The plant Adhatoda vasica L. (a medicinal plant) was selected and the leaves of this plant were used for development of linear model for leaf area using Leaf Area Meter (LAM) software. Planimetric parameters (length, length2, width and width2) and gravimetric (dry weight and water content) parameters are considered for the development of linear model for this plant species. Single factor ANOVA and linear correlations were worked out using these parameters and leaf area. The plant was showed significant relationship with the parameters studied. The best correlation as represented by regression coefficient (R2) was used and improved R2 is worked out. It is observed that with increase in leaf area, water content is also increased and showed best correlation with the leaf area. Thus water content can be taken as a parameter for developing linear model for leaf area is concluded.

scholarly journals Development of Accurate BSIM4 Noise Parameters for CMOS 0.13-µm Transistors in Below 3-GHz LNA Application

2018 ◽  
Vol 10 (3) ◽  
pp. 925
Author(s):  
Asmaa Nur Aqilah Zainal Badri ◽  
Norlaili Mohd Noh ◽  
Shukri Bin Korakkottil Kunhi Mohd ◽  
Asrulnizam Abd Manaf ◽  
Arjuna Marzuki ◽  
...  
Keyword(s):  
Thermal Noise ◽  
Noise Figure ◽  
Noise Model ◽  
Ic Design ◽  
Noise Parameters ◽  
Specific Frequency ◽  
Minimum Noise ◽  
Minimum Noise Figure ◽  
Selection Of

Accurate transistor thermal noise model is crucial in IC design as it allows accurate selection of transistors for specific frequency application. The accuracy of the model is represented by the similarity between the simulated and the measured noise parameters (NPs). This work was based on a problem faced by a foundry concerning the dissimilarities between the measured and simulated NPs, especially minimum noise figure (NF<sub>min</sub>) for frequencies below 3 GHz.

scholarly journals Online Parameter Identification of the Lithium-Ion Battery with Refined Instrumental Variable Estimation

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
An Wen ◽  
Jinhao Meng ◽  
Jichang Peng ◽  
Lei Cai ◽  
Qian Xiao
Keyword(s):  
Instrumental Variable ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Parameters Estimation ◽  
Measurement Noise ◽  
Recursive Least Squares ◽  
Ar Model ◽  
Noise Model ◽  
Li Ion Battery ◽  
Li Ion

Refined Instrumental Variable (RIV) estimation is applied to online identify the parameters of the Equivalent Circuit Model (ECM) for Lithium-ion (Li-ion) battery in this paper, which enables accurate parameters estimation with the measurement noise. Since the traditional Recursive Least Squares (RLS) estimation is extremely sensitive to the noise, the parameters in the ECM may fail to converge to their true values under the measurement noise. The RIV estimation is implemented in a bootstrap form, which alternates between the estimation in the system model and the noise model. The Box-Jenkins model of the Li-ion battery transformed from the two RC ECM is selected as the transfer function model for the RIV estimation in this paper. The errors of the two RC ECM are independently generated by the residual of high-order Auto Regressive (AR) model estimation. With the benefit of a series of auxiliary models, the data filtering technology can prefilter the measurement and increase the robustness of the parameters against the noise. Reasonable parameters are possible to be obtained regardless of the noise in the measurement by RIV. Simulation and experimental tests on a LiFePO4 battery validate the efficiency of RIV for parameter online identification compared with traditional RLS.

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