A band-selective CMOS low-noise amplifier with current reuse gm boosting technique for 3-5 GHz UWB receivers

529-537The authors have proposed a 3-5 GHz ultra-wideband (UWB) low power and low noise amplifier (LNA) with the TSMC 0.18 μm RF CMOS process, which uses a novel dual input matching network for wideband matching. We have used a current-reuse gm-boosted common-gate topology and shunt-shunt feedback common-source output buffer to improve gain and noise figure with low power dissipation. The proposed dual input matching gm-boosted common-gate LNA has been efficient bandwidth to cover UWB band. It has required less inductors or amplification stages to increase bandwidth as compared with the conventional UWB common-gate LNAs. The broadband input stage has been able to be switched to three frequency bands with capacitive switches. The capacitive switch has replaced a large inductor to resonate at lower frequency band. The band-selective LNA has shown linearity improvement by attenuating the undesired interference of a wideband gain circuit and using less inductors. Simulated performance has shown the gains of 15.9, 17.6, and 16.9 dB, and the noise figures of 3.38, 3.28, and 3.27 dB at the 3.432, 3.960, and 4.488 GHz frequency bands, respectively. The proposed UWB LNA has consumed 5 mW from a 1.8-V power supply

A band-selective CMOS low-noise amplifier with current reuse gm boosting technique for 3-5 GHz UWB receivers

The authors have proposed a 3-5 GHz ultra-wideband (UWB) low power and low noise amplifier (LNA) with the TSMC 0.18 μm RF CMOS process, which uses a novel dual input matching network for wideband matching. We have used a current-reuse gm-boosted common-gate topology and shunt-shunt feedback common-source output buffer to improve gain and noise figure with low power dissipation. The proposed dual input matching gm-boosted common-gate LNA has been efficient bandwidth to cover UWB band. It has required less inductors or amplification stages to increase bandwidth as compared with the conventional UWB common-gate LNAs. The broadband input stage has been able to be switched to three frequency bands with capacitive switches. The capacitive switch has replaced a large inductor to resonate at lower frequency band. The band-selective LNA has shown linearity improvement by attenuating the undesired interference of a wideband gain circuit and using less inductors. Simulated performance has shown the gains of 15.9, 17.6, and 16.9 dB, and the noise figures of 3.38, 3.28, and 3.27 dB at the 3.432, 3.960, and 4.488 GHz frequency bands, respectively. The proposed UWB LNA has consumed 5 mW from a 1.8-V power supply

Fully ion-implanted InP JFET with buried p-layer

A buried p-layer has been successfully implemented in a fully ion implanted InP JFET for the first time. Using Be co-implanted with Si, a sharp channel profile is obtained. The saturation current has been reduced and the pinch-off characteristic has been improved with a slight decrease in transconductance and cutoff frequency. The equhalent circuits for the JFET with and without the buried p-layer are compared

Three-stage InP JFET amplifier for receiver optoelectronic integrated circuits

Three-stage InP JFET amplifiers have been fabricated on semi-insulating InP using ion implantation. The amplifiers show dc gain of 43-65 calculated from amplifier transfer characteristics. From highfrequency measurements, a 3-dB bandwidth of 400 MHz and a gain of 38 have been measured from the amplifiers.The authors would like to thank R. A. Resta for dielectric depositions, D. Ingersoll and D. DeBlis for help in processing, F. Elizabeth and J. Collis for help in layout of test patterns, and B. C. DeLoach for support and encouragement

High-speed signal switching with a monolithic integrated p-i-n/amp/switch on indium phosphide

Operation of an optoelectronic integrated circuit which includes two p-i-ns, preamplifiers, 2 x 2 crosspoint .switch, and output buffers has been demonstrated. These circuits have been fabricated in semi-insulating 1nP:Fe substrates by vapor phase epitaxy and ion implantation using a planar horizontally integrated technology. Signals modulated at 150 MHz are shown to be switched at 15 MHz, with the circuits capable of detecting and passing data modulated at - 1 GHz

Subdividing Stress Groups into Eustress and Distress Groups Using Laterality Index Calculated from Brain Hemodynamic Response

A stress group should be subdivided into eustress (low-stress) and distress (high-stress) groups to better evaluate personal cognitive abilities and mental/physical health. However, it is challenging because of the inconsistent pattern in brain activation. We aimed to ascertain the necessity of subdividing the stress groups. The stress group was screened by salivary alpha-amylase (sAA) and then, the brain’s hemodynamic reactions were measured by functional near-infrared spectroscopy (fNIRS) based on the near-infrared biosensor. We compared the two stress subgroups categorized by sAA using a newly designed emotional stimulus-response paradigm with an international affective picture system (IAPS) to enhance hemodynamic signals induced by the target effect. We calculated the laterality index for stress (LIS) from the measured signals to identify the dominantly activated cortex in both the subgroups. Both the stress groups exhibited brain activity in the right frontal cortex. Specifically, the eustress group exhibited the largest brain activity, whereas the distress group exhibited recessive brain activity, regardless of positive or negative stimuli. LIS values were larger in the order of the eustress, control, and distress groups; this indicates that the stress group can be divided into eustress and distress groups. We built a foundation for subdividing stress groups into eustress and distress groups using fNIRS

Explainable Convolutional Neural Network to Investigate Age-Related Changes in Multi-Order Functional Connectivity

Functional connectivity (FC) is a potential candidate that can increase the performance of brain-computer interfaces (BCIs) in the elderly because of its compensatory role in neural circuits. However, it is difficult to decode FC by the current machine learning techniques because of a lack of physiological understanding. To investigate the suitability of FC in BCIs for the elderly, we propose the decoding of lower- and higher-order FC using a convolutional neural network (CNN) in six cognitive-motor tasks. The layer-wise relevance propagation (LRP) method describes how age-related changes in FCs impact BCI applications for the elderly compared to younger adults. A total of 17 young adults 24.5±2.7 years and 12 older 72.5±3.2 years adults were recruited to perform tasks related to hand-force control with or without mental calculation. The CNN yielded a six-class classification accuracy of 75.3% in the elderly, exceeding the 70.7% accuracy for the younger adults. In the elderly, the proposed method increased the classification accuracy by 88.3% compared to the filter-bank common spatial pattern. The LRP results revealed that both lower- and higher-order FCs were dominantly overactivated in the prefrontal lobe, depending on the task type. These findings suggest a promising application of multi-order FC with deep learning on BCI systems for the elderly