Design and Temperature Reliability Testing for A 0.6–2.14GHz Broadband Power Amplifier

Lin, Qian; Cheng, Qian‐Fu; Gu, Jifa; Zhu, Yi; Chen, Chao; Fu, Haipeng

doi:10.1007/s10836-016-5571-7

Cited by 19 publications

(14 citation statements)

References 16 publications

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“…However, it is still very effective and convenient for some application scenarios that need to know the trend and range of RF amplifier specifications quickly and qualitatively. On the other hand, another method is to directly obtain the specifications of RF amplifiers at different temperatures by measurement [ 20 ]. For example, Li et al measured the specifications of power amplifiers at 0 °C, 50 °C, 75 °C and 100 °C [ 20 , 21 ], and Kumar et al measured the specifications of low-noise amplifiers at −40 °C, 27 °C, 75 °C and 100 °C [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, another method is to directly obtain the specifications of RF amplifiers at different temperatures by measurement [ 20 ]. For example, Li et al measured the specifications of power amplifiers at 0 °C, 50 °C, 75 °C and 100 °C [ 20 , 21 ], and Kumar et al measured the specifications of low-noise amplifiers at −40 °C, 27 °C, 75 °C and 100 °C [ 22 ]. This method can be more accurate in knowing the specifications of RF amplifiers at different temperatures, but the measurement process takes more time and is also constrained by the measurement environment to measure RF amplifier specifications at each temperature.…”

Section: Introductionmentioning

confidence: 99%

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Modeling of Key Specifications for RF Amplifiers Using the Extreme Learning Machine

2022

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The amplifier is a key component of the radio frequency (RF) front-end, and its specifications directly determine the performance of the system in which it is located. Unfortunately, amplifiers’ specifications degrade with temperature and even lead to system failure. To study how the system failure is affected by the amplifier specification degradation, it is necessary to couple the amplifier specification degradation into the system optimization design. Furthermore, to couple the amplifier specification degradation into the optimal design of the system, it is necessary to model the characteristics of the amplifier specification change with temperature. In this paper, the temperature characteristics of two amplifiers are modeled using an extreme learning machine (ELM), and the results show that the model agrees well with the measurement results and can effectively reduce measurement time and cost.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling of Key Specifications for RF Amplifiers Using the Extreme Learning Machine

2022

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“…According to previous papers, investigation on temperature behavior is still a hot issue [ 9 , 10 ]. However, the common temperature ranges, depending on the extreme temperature, are −40–120 °C, −25–125 °C, 10–90 °C, 20–120 °C or 25–125 °C and so on [ 8 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. Meanwhile, the equal interval temperatures are adopted [ 8 , 15 , 16 , 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Investigation on Temperature Behavior for a GaAs E-pHEMT MMIC LNA

Lin

Jia

Wu³

et al. 2022

Micromachines

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In order to investigate the temperature behavior for monolithic microwave integrated circuits (MMICs) under alpine conditions, the performance parameters of a 0.4–3.8 GHz gallium arsenide (GaAs) enhancement pseudomorphic high-electron-mobility transistor (E-pHEMT) low-noise amplifier (LNA) are tested at different temperatures. The typical temperatures of −39.2 °C, −32.9 °C, −25.3 °C, −11.3 °C, −4.9 °C, 0 °C and 23 °C are chosen as the alpine condition. The major performance indexes including the direct current (DC) characteristics, S-parameters, stability, radio frequency (RF) output characteristics, output third-order intersection point (OIP3) and noise figure (NF), which were inspected and analyzed in detail. The results show that the DC characteristics, small-signal gain (S21), RF output characteristics and NF all deteriorate with the rising temperature due to the decrease in two-dimensional electron gas mobility (). Contrary to this trend, the special design makes stability and OIP3 increase. For further application of this MMIC LNA under alpine conditions, several measures can be utilized to remedy performance degradation. This paper can provide some significant engineering value for the reliable design of MMICs.

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“…Suppose a PA used in a system does not perform as designed/expected under certain environmental situations. In that case, the system's performances will be corrupted, even if the system is likely to fail [35]- [36]. Therefore, it is desirable to get the PA's performance degradations concerning the temperature and humidity changes in advance.…”

Section: Introductionmentioning

confidence: 99%

Characteristics Modeling of GaN Class-AB Dual-Band PA Under Different Temperature and Humidity Conditions

Zhou

Jha

2021

IEEE Access

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As the technology scales down, besides the CAD tools and design guidelines, understanding circuit performance degradation as a consequence of transistor degradation becomes essential for designers. Due to several adverse environmental conditions, the study of performance degradation in the power amplifier (PA) is very demanding research. In this paper, an RF PA is experimentally studied to observe various characteristic degradations in a broad range of operating temperature and humidity conditions. Based on a few key measurement points, a measurement-based modeling method is proposed to help designers make intelligent decisions to minimize the performance degradation effects. This method uses four two-dimensional interpolation models, and the results show that the prediction results of the four planar interpolation models are in good agreement with the measurement results. The results presented in this article help select design models for the RF power amplifier that can analyze the performance degradation of the transistor parameters in advance. Cubic and spline interpolation has the highest model accuracy among the four two-dimensional models, while the nearest interpolation offers the shortest training time.

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Design and Temperature Reliability Testing for A 0.6–2.14GHz Broadband Power Amplifier

Cited by 19 publications

References 16 publications

Modeling of Key Specifications for RF Amplifiers Using the Extreme Learning Machine

Modeling of Key Specifications for RF Amplifiers Using the Extreme Learning Machine

Investigation on Temperature Behavior for a GaAs E-pHEMT MMIC LNA

Characteristics Modeling of GaN Class-AB Dual-Band PA Under Different Temperature and Humidity Conditions

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