Design of Cryogenic LNAs for High Linearity in Space Applications

Çağlar, Alican; Yelten, Mustafa Berke

doi:10.1109/tcsi.2019.2936506

Cited by 32 publications

(9 citation statements)

References 31 publications

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“…Finally, the results of this study are compared with state-of-the-art LNAs given in Table 1. In addition, the extra technical information about the LNA, such as its Figure of Merit (FOM), is calculated [33][34][35] and presented in Appendix C (Fig. 12).…”

Section: Resultsmentioning

confidence: 99%

Design of ultra-low noise amplifier for quantum applications (QLNA)

Salmanogli,

Sirat

2024

Quantum Inf Process

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The present article primarily focuses on the design of an ultra-low-noise amplifier specifically tailored for quantum applications. The circuit design places a significant emphasis on improving the noise figure, as quantum-associated applications require the circuit's noise temperature to be around 0.4 K. This requirement aims to achieve performance comparable to the Josephson Junction amplifier. Although this task presents considerable challenges, the work concentrates on engineering the circuit to minimize mismatch and reflection coefficients, while simultaneously enhancing circuit transconductance. These efforts aim to improve the noise figure as efficiently as possible. The results of this study indicate the possibility of achieving a noise figure of approximately 0.009 dB for a unique circuit design operating at 10 K. In a departure from traditional approaches, this study employs quantum mechanical theory to analyze the circuit comprehensively. By employing quantum theory, the researchers derive relationships that highlight the crucial quantities upon which the circuit design should focus to optimize the noise figure. For example, the circuit's gain power, which depends on the circuit's photonic modes, is theoretically derived and found to affect the noise figure directly. Ultimately, by merging quantum theory with engineering approaches, this study successfully designs a highly efficient circuit that significantly minimizes the noise figure in a quantum application setting.

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Section: Resultsmentioning

confidence: 99%

Design of ultra-low noise amplifier for quantum applications (QLNA)

Salmanogli,

Sirat

2024

Quantum Inf Process

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“…We do the performance analysis of the proposed design of LNA with respect to state-of-the-art LNAs near our design band. We consider the design of LNAs recently published [52][53][54][55][56][57] for comparative study. Here, only the class of single-stage amplifiers near the band range 1.3-2.3 GHz are selected and compared based on the figure of merit (FoM) defined by the International Technology Roadmap for Semiconductor (ITRS).…”

Section: Measured Resultsmentioning

confidence: 99%

“…We consider different LNAs working in a band near about 1.3 to 2.3 GHz across the device technologies CMOS 53,55,57 and GaAs 52 to compare the performance of our proposed LNA, refer to Table 5. FoM is calculated for the considered LNAs and our proposed LNA using Equation (21).…”

Section: Measured Resultsmentioning

confidence: 99%

A multi‐variable double impedance matching network design algorithm with design example of a low noise amplifier

Bajpai

Chauhan

2022

Int J RF Mic Comp-Aid Eng

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In this article, we propose a matching network design algorithm based on the segmentation of the real and imaginary part of optimum source impedance curve with respect to space variable x and frequency ω, respectively. The impedance curve (comprising of real and imaginary parts) is approximated as a collection of n linear segments, represented by the weighted sum of n semiinfinite linear functions. Using the numerical method, optimum weight vectors that maximize transducer power gain are obtained to model the real and imaginary parts of the source impedance curve. We get the values of optimum weight vectors and the rational input impedance function for the matching network, which are then synthesized in the desired topology by a continued partial fraction. Experimentally, we validate the novelty of the proposed method by designing matching networks of a wideband custom monolithic microwave integrated circuit (MMIC) low noise amplifier (LNA) in 1.3-2.3 GHz frequency band. The measured results of the designed LNA are significantly close to the simulated results. We bias our LNA at (5 V, 150 mA) and achieve a maximum noise figure of 1.25 dB, OP 1dB of 26 dBm, and an average TOI of 38 dBm. Moreover, our design of custom LNA MMIC has an integrated ESD structure while occupying only 0.32 mm 2 of chip area.

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“…The power amplifier (PA) is a critical component of wireless communication systems, and previous studies have shown that cryogenic effects can significantly impact its operation by changing transistor parameters and causing performance deviations from nominal operating characteristics [2], [3], [4]. Although there have been few works in the literature addressing PA design for environments with extreme temperatures, a significant amount of research has been done on cryogenic low-noise amplifier (LNA) design for very low-noise applications, either through the use of alternative technologies like SiGe HBTs or by incorporating cryogenic MOSFET modeling data into the design process [5], [6], [7], [8], [9], [10]. In this paper, we propose leveraging a reinforcement learning agent to program a highly configurable PA design that can operate across a wide temperature range.…”

Section: Introductionmentioning

confidence: 99%

Deep Reinforcement Learning on FPGA for Self-Healing Cryogenic Power Amplifier Control

Shen

et al. 2023

IEEE Open J. Circuits Syst.

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Wireless sensing and communication for space exploration in areas inaccessible to human often suffer from severe performance degradation due to the cryogenic effects on the transmitters' circuits. To survive extreme temperatures, programmable radio frequency (RF) power amplifiers (PA) can be built into the transmitter, and intelligent PA controllers need to be integrated into the system to interact with the environment and restore the PA's functionalities. This problem can be modeled as the controller acts (control the PA) in an environment to maximize the reward (signal quality), and it is most suitable to use reinforcement learning as a solution. This paper presents a cryogenic and energy-efficient reinforcement learning (RL) module on Field Programmable Gate Arrays (FPGA) that can directly program the PA. By characterizing a self-healing PA in a liquid nitrogen environment, we generated an RF signal data set and built an interactive RL environment to model the PA's behaviors across its configurations and cryogenic temperatures down to −197 • C. We developed a deep RL model with a high generalization capability introduced by the neural networks to control the PA and restore its performance. The RL model with fixed-point training and inference is implemented on FPGA to survive the cryogenic conditions and carry out fast and low-power training and inference for PA control. All functionalities of the programmed FPGA operate correctly in the cryogenic testing environment.INDEX TERMS Deep reinforcement learning, quantized neural networks, quantized training, fixed-point arithmetic, FPGA, power amplifier, cryogenic circuits.

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Design of Cryogenic LNAs for High Linearity in Space Applications

Cited by 32 publications

References 31 publications

Design of ultra-low noise amplifier for quantum applications (QLNA)

Design of ultra-low noise amplifier for quantum applications (QLNA)

A multi‐variable double impedance matching network design algorithm with design example of a low noise amplifier

Deep Reinforcement Learning on FPGA for Self-Healing Cryogenic Power Amplifier Control

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