2013
DOI: 10.4103/0377-2063.118022
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An ultra-low-power integrated RF receiver for multi-standard wireless applications

Abstract: In this paper, an ultra-low-power integrated RF front end for multi-standard is proposed. It contains a current-reuse low-noise amplifier (LNA) and a single-balanced mixer. The double resonances network helps to achieve a good input impedance matching in the required band and suppress out-of-band noise. The stacked common source (CS) LNA is adopting current-reuse of the two amplifier stages and re-using bleeding current of the mixer, which save working current considerably. By employing forward body bias techn… Show more

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Cited by 3 publications
(1 citation statement)
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“…Non-linear systems present a significant challenge for modeling, analysis, and control because their output cannot be described simply by a linear relationship with the input, and their dynamics may exhibit complex behaviors such as chaos or periodicity. The study of non-linear systems is critical to many fields, including control engineering (Xiao et al, 2017b;Zhou et al, 2022), signal processing (Jin, 2014;Luo and Xie, 2017), dynamics analysis (Tan and Dai, 2016;Tan et al, , 2019aLu et al, 2020), and communication systems (Jin and Yu, 2012;Jin and Fu, 2013;Jin et al, 2015b;Zhao et al, 2020;Xiang et al, 2022), owing to the following properties.…”
Section: Neural Network For Non-linear System Solvingmentioning
confidence: 99%
“…Non-linear systems present a significant challenge for modeling, analysis, and control because their output cannot be described simply by a linear relationship with the input, and their dynamics may exhibit complex behaviors such as chaos or periodicity. The study of non-linear systems is critical to many fields, including control engineering (Xiao et al, 2017b;Zhou et al, 2022), signal processing (Jin, 2014;Luo and Xie, 2017), dynamics analysis (Tan and Dai, 2016;Tan et al, , 2019aLu et al, 2020), and communication systems (Jin and Yu, 2012;Jin and Fu, 2013;Jin et al, 2015b;Zhao et al, 2020;Xiang et al, 2022), owing to the following properties.…”
Section: Neural Network For Non-linear System Solvingmentioning
confidence: 99%