An Ultra-wideband Low-power Low-noise Amplifier Linearized by Adjusted Derivative Superposition and Feedback Techniques

Alirezapoori, Mohsen and Hayati, Mohsen and Imani, Mohammad A. and Shama, Farzin and Almasi, Pouria (2023) An Ultra-wideband Low-power Low-noise Amplifier Linearized by Adjusted Derivative Superposition and Feedback Techniques. ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 11 (2). pp. 201-209. ISSN 2410-9355

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Abstract

Ultra-wideband (UWB) applications require low-power and low-noise amplifiers (LNAs) that can operate over a wide frequency range. However, conventional LNAs often suffer from poor linearity and high-power consumption. This research work proposes a novel LNA design that uses the adjusted derivative superposition (DS) technique and feedback to improve the linearity and reduce the power consumption of UWB LNAs. The DS technique enhances the third-order intermodulation (IM3) cancellation by adjusting the bias currents of the transistors, whereas the feedback improves the stability and input matching of the LNA. The LNA is implemented using a degenerated common source topology in a 180 nm standard CMOS technology. The simulation results show that the LNA achieves a power gain of 10–12.2 dB, an input third-order intercept point (IIP3) of about 12 dBm, and a noise figure of less than 2.5 dB over the UWB frequency band of 3.1–10.6 GHz. The input reflection coefficient is less than -10 dB, and the power consumption is 11.6 mW with a 1.5 V power supply. The designed LNA offers a novel and innovative solution for UWB applications that significantly improve the performance and efficiency of UWB LNAs whereas reducing the cost and complexity of implementation.

Item Type:	Article
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Uncontrolled Keywords:	Derivative superposition technique, Low-noise amplifier, Low-Power, Linearization
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	ARO-The Scientific Journal of Koya University > VOL 11, NO 2 (2023)
Depositing User:	Dr Salah Ismaeel Yahya
Date Deposited:	04 Jan 2024 09:03
Last Modified:	04 Jan 2024 09:03
URI:	http://eprints.koyauniversity.org/id/eprint/452

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