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an-QNA: An Adaptive Nesterov Quasi-Newton Acceleration-Optimized CMOS LNA for 65 nm Automotive Radar Applications.
- Source :
- Sensors (14248220); Sep2024, Vol. 24 Issue 18, p6141, 26p
- Publication Year :
- 2024
-
Abstract
- An adaptive Nesterov quasi-Newton acceleration (an-QNA)-optimized low-noise amplifier (LNA) is proposed in this paper. An optimized single-ended-to-differential two-stage LNA circuit is presented. It includes an improved post-linearization (I<subscript>PL</subscript>) technique to enhance the linearity. Traditional methods like conventional quasi-Newton (c-QN) often suffer from slow convergence and the tendency to get trapped in local minima. However, the proposed an-QNA method significantly accelerates the convergence speed. Furthermore, in this paper, modifications have been made to the an-QNA algorithm using a quadratic estimation to guarantee global convergence. The optimized an-QNA-based LNA, using standard 65 nm CMOS technology, achieves a simulated gain of 17.5 dB, a noise figure (NF) of 3.7 dB, and a 1 dB input compression point (IP<subscript>1</subscript>dB) of −13.1 dBm. It is also noted that the optimized LNA achieves a measured gain of 12.9 dB and an NF of 4.98 dB, and the IP<subscript>1</subscript>dB is −17.8 dB. The optimized LNA has a chip area of 0.67 mm<superscript>2</superscript>. [ABSTRACT FROM AUTHOR]
- Subjects :
- LOW noise amplifiers
ROAD vehicle radar
SPEED
NOISE
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 24
- Issue :
- 18
- Database :
- Complementary Index
- Journal :
- Sensors (14248220)
- Publication Type :
- Academic Journal
- Accession number :
- 179964805
- Full Text :
- https://doi.org/10.3390/s24186141