An efficient design of 45-nm CMOS low-noise charge sensitive amplifier for wireless receivers

<p>Amplifiers are widely used in signal receiving circuits, such as antennas, medical imaging, wireless devices and many other applications. However, one of the most challenging problems when building an amplifier circuit is the noise, since it affects the quality of the intended received signal in most wireless applications. Therefore, a preamplifier is usually placed close to the main sensor to reduce the effects of interferences and to amplify the received signal without degrading the signal-to-noise ratio. Although different designs have been optimized and tested in the literature, all of them are using larger than 100 nm technologies which have led to a modest performance in terms of equivalent noise charge (ENC), gain, power consumption, and response time. In contrast, we consider in this paper a new amplifier design technology trend and move towards sub 100 nm to enhance its performance. In this work, we use a pre-well-known design of a preamplifier circuit and rebuild it using 45 nm CMOS technology, which is made for the first time in such circuits. Performance evaluation shows that our proposed scaling technology, compared with other scaling technology, extremely reduces ENC of the circuit by more than 95%. The noise spectral density and time resolution are also reduced by 25% and 95% respectively. In addition, power consumption is decreased due to the reduced channel length by 90%. As a result, all of those enhancements make our proposed circuit more suitable for medical and wireless devices.</p>

Kernel Conversion for Robust Quantitative Measurements of Archived Chest Computed Tomography Using Deep Learning-Based Image-to-Image Translation

Chest computed tomography (CT) is used to screen for lung cancer and evaluate pulmonary and extra-pulmonary abnormalities such as emphysema and coronary artery calcification, particularly in smokers. In real-world practice, lung abnormalities are visually assessed using high-contrast thin-slice images which are generated from raw scan data using sharp reconstruction kernels with the sacrifice of increased image noise. In contrast, accurate CT quantification requires low-contrast thin-slice images with low noise, which are generated using soft reconstruction kernels. However, only sharp-kernel thin-slice images are archived in many medical facilities due to limited data storage space. This study aimed to establish deep neural network (DNN) models to convert sharp-kernel images to soft-kernel-like images with a final goal to reuse historical chest CT images for robust quantitative measurements, particularly in completed previous longitudinal studies. By using pairs of sharp-kernel (input) and soft-kernel (ground-truth) images from 30 patients with chronic obstructive pulmonary disease (COPD), DNN models were trained. Then, the accuracy of kernel conversion based on the established DNN models was evaluated using CT from independent 30 smokers with and without COPD. Consequently, differences in CT values between new images converted from sharp-kernel images using the established DNN models and ground-truth soft-kernel images were comparable with the inter-scans variability derived from repeated phantom scans (6 times), showing that the conversion error was the same level as the measurement error of the CT device. Moreover, the Dice coefficients to quantify the similarity between low attenuation voxels on given images and the ground-truth soft-kernel images were significantly higher on the DNN-converted images than the Gaussian-filtered, median-filtered, and sharp-kernel images (p &lt; 0.001). There were good agreements in quantitative measurements of emphysema, intramuscular adipose tissue, and coronary artery calcification between the converted and the ground-truth soft-kernel images. These findings demonstrate the validity of the new DNN model for kernel conversion and the clinical applicability of soft-kernel-like images converted from archived sharp-kernel images in previous clinical studies. The presented method to evaluate the validity of the established DNN model using repeated scans of phantom could be applied to various deep learning-based image conversions for robust quantitative evaluation.

Design and Implementation of Charge Pump Phase-Locked Loop Frequency Source Based on GaAs pHEMT Process

This paper realized a charge pump phase locked loop (CPPLL) frequency source circuit based on 0.15 μm Win GaAs pHEMT process. In this paper, an improved fully differential edge-triggered frequency discriminator (PFD) and an improved differential structure charge pump (CP) are proposed respectively. In addition, a low noise voltage-controlled oscillator (VCO) and a static 64:1 frequency divider is realized. Finally, the phase locked loop (PLL) is realized by cascading each module. Measurement results show that the output signal frequency of the proposed CPPLL is 3.584 GHz–4.021 GHz, the phase noise at the frequency offset of 1 MHz is −117.82 dBc/Hz, and the maximum output power is 4.34 dBm. The chip area is 2701 μm × 3381 μm, and the power consumption is 181 mw.

Investigation of Acoustic Properties of Different Types of Low-Noise Road Surfacers under In Situ and Laboratory Conditions

Current literature on the performance characteristics of road surfaces is primarily focused on evenness, roughness and technical durability. However, other important surface properties require analysis, including noisiness, which is an important feature of the environmental impact of vehicular traffic around roads. This can be studied using various methods by which road noise phenomena are investigated. The method used to measure the noise performance of road surfaces herein is the Statistical Pass-By (SPB) method, as described in ISO 11819-1:1997. The impedance tube method was used for sound absorption testing, as described in ISO 13472-2:2010. These tests were performed under a variety of conditions: in situ and in laboratory. The existence of relationships between them can be helpful in selecting surfaces for noise reduction. Preliminary surface noise tests can be performed in the laboratory with samples consisting of various compounds. This is less expensive and faster than doing so on purpose-built surfaces. The paper presents study results for sound absorption coefficients of various types of low-noise surfaces in in situ conditions (on an experimental section and on operated road sections) and in the laboratory setting. The results of the tests performed on the operational sections were compared to the results of the surface impact on road noise using the SPB method. The correlations between the test results help confirm the feasibility of road surface pre-testing in the laboratory and the relation to tests performed using the SPB method under typical operating conditions.

Thin MAPb0.5Sn0.5I3 Perovskite Single Crystals for Sensitive Infrared Light Detection

Metal halide perovskite single-crystal detectors have attracted increasing attention due to the advantages of low noise, high sensitivity, and fast response. However, the narrow photoresponse range of widely investigated lead-based perovskite single crystals limit their application in near-infrared (NIR) detection. In this work, tin (Sn) is incorporated into methylammonium lead iodide (MAPbI3) single crystals to extend the absorption range to around 950 nm. Using a space-confined strategy, MAPb0.5Sn0.5I3 single-crystal thin films with a thickness of 15 μm is obtained, which is applied for sensitive NIR detection. The as-fabricated detectors show a responsivity of 0.514 A/W and a specific detectivity of 1.4974×1011 cmHz1/2/W under 905 nm light illumination and –1V. Moreover, the NIR detectors exhibit good operational stability (∼30000 s), which can be attributed to the low trap density and good stability of perovskite single crystals. This work demonstrates an effective way for sensitive NIR detection.

A Longitudinal-Bending Hybrid Linear Ultrasonic Motor and Its Driving Characteristic

As a new type of driver, linear ultrasonic motor (LUSM) is widely used in the high-tech field because of its low speed, high thrust, low noise, and no electromagnetic interference. However, as an actuator used in microdevices, most of the existing LUSMs are large in size and not compact in structure. In order to overcome these limitations, a new structure of linear ultrasonic motor’s stator is developed in this paper. The stator is similar to a tuning fork structure, which is divided into three parts: two driving feet, two driving legs, and the driving body. By using the first-order longitudinal vibration mode of the whole stator and the unique partial second-order bending vibration mode of the driving legs to achieve vibration mode degeneracy, a mode hybrid linear ultrasonic motor that is easy to miniaturize is proposed. Its working principle is analyzed. The dynamic analysis of the stator is carried out by using finite element software. The structure dimension of the stator and the driving frequency under the working mode are determined. At the same time, the feasibility of driving feet synthesizing elliptical motion is verified theoretically and experimentally. In addition, the LUSM test setup is built. The effects of driving frequency and Vpp on stator stall force and average velocity are studied. The results show that the maximum stall force can reach 99 mN, and the average velocity of the motor is 88.67 mm/s with Vpp = 320 V and driving frequency 80.2 kHz. The proposed LUSM is appropriate for use in occasions with quick return characteristics, like the controlling valve or nozzle of the printer. The research results provide guidance for the stator design of the linear ultrasonic motor.

Guidelines for the LTO Noise Assessment of Future Civil Supersonic Aircraft in Conceptual Design

One of the most critical regulatory issues related to supersonic flight arises from limitations imposed by community noise acceptability. The most efficient way to ensure that future supersonic aircraft will meet low-noise requirements is the verification of noise emissions from the early stages of the design process. Therefore, this paper suggests guidelines for the Landing and Take-Off (LTO) noise assessment of future civil supersonic aircraft in conceptual design. The supersonic aircraft noise model is based on the semi-empirical equations employed in the early versions of the Aircraft NOise Prediction Program (ANOPP) developed by NASA, whereas sound attenuation due to atmospheric absorption has been considered in accordance with SAE ARP 866 B. The simulation of the trajectory leads to the prediction of the aircraft noise level on ground in terms of several acoustic metrics (LAmax, SEL, PNLTM and EPNL). Therefore, a dedicated validation has been performed, selecting the only available supersonic aircraft of the Aircraft Noise and Performance database (ANP), that is, the Concorde, through the matching with Noise Power Distance (NPD) curves for LAmax and SEL, obtaining a maximum prediction error of ±2.19%. At least, an application to departure and approach procedures is reported to verify the first noise estimations with current noise requirements defined by ICAO at the three certification measurement points (sideline, flyover, approach) and to draw preliminary considerations for future low-noise supersonic aircraft design.