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학술논문Journal of Electromagnetic Engineering and Science2009.03 발행KCI 피인용 1

A 0.18-μm CMOS UWB LNA Combined with High-Pass-Filter

A 0.18-μm CMOS UWB LNA Combined with High-Pass-Filter

김정연(동아대학교); 김창완(동아대학교)

9권 1호, 7~10쪽

초록

An Ultra-WideBand(UWB) Low-Noise Amplifier(LNA) is proposed and is implemented in a 0.18-μm CMOS technology. The proposed UWB LNA provides excellent wideband characteristics by combining a High-Pass Filter (HPF) with a conventional resistive-loaded LNA topology. In the proposed UWB LNA, the bell-shaped gain curve of the overall amplifier is much less dependent on the frequency response of the HPF embedded in the input stage. In addition, the adoption of fewer on-chip inductors in the input matching network permits a lower noise figure and a smaller chip area. Measurement results show a power gain of +10 dB and an input return loss of more than -9 dB over 2.7 to 6.2 GHz, a noise figure of 3.1 dB at 3.6 GHz and 7.8 dB at 6.2 GHz, an input P1dB of -12 dBm, and an IIP3 of -0.2 dBm, while dissipating only 4.6 mA from a 1.8-V supply.

Abstract

An Ultra-WideBand(UWB) Low-Noise Amplifier(LNA) is proposed and is implemented in a 0.18-μm CMOS technology. The proposed UWB LNA provides excellent wideband characteristics by combining a High-Pass Filter (HPF) with a conventional resistive-loaded LNA topology. In the proposed UWB LNA, the bell-shaped gain curve of the overall amplifier is much less dependent on the frequency response of the HPF embedded in the input stage. In addition, the adoption of fewer on-chip inductors in the input matching network permits a lower noise figure and a smaller chip area. Measurement results show a power gain of +10 dB and an input return loss of more than -9 dB over 2.7 to 6.2 GHz, a noise figure of 3.1 dB at 3.6 GHz and 7.8 dB at 6.2 GHz, an input P1dB of -12 dBm, and an IIP3 of -0.2 dBm, while dissipating only 4.6 mA from a 1.8-V supply.

발행기관:
한국전자파학회
분류:
전자/정보통신공학

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A 0.18-μm CMOS UWB LNA Combined with High-Pass-Filter | Journal of Electromagnetic Engineering and Science 2009 | AskLaw | 애스크로 AI