Design-window methodology for inductorless noise-cancelling CMOS LNAs

Martinez-Perez, A. D. (Universidad de Zaragoza) ; Aznar, F. (Universidad de Zaragoza) ; Flandre, D. ; Celma, S. (Universidad de Zaragoza)

Resumen: This paper presents an optimization methodology for inductorless noise-cancelling CMOS Low-Noise Amplifiers (LNA), whose performance typically depends on a tight balance in the design of two transistor stages. Due to the different functions of the two parts, noise-cancelling amplifiers become very difficult to analyze in detail by closed-form expressions or straight simulations: each section significantly affects the results of the other. In addition, opposed specifications, such as gain and cut-off frequency, suppose another grade of complexity due to the interplay of the two branches of the circuit. As a solution, the proposed methodology uses a visualization of the design window in 2-dimensional space to optimize the different parameters of the specifications without compromising the others. All specification constraints are represented in a single figure instead of one graph per parameter. Compared with most optimization methods, the design window methodology observes the design span instead of isolated design points that might not guarantee feasibility. Furthermore, as a simulation-driven exploration method, it benefits from complete device models with high-order effects that would be too complex to include in analytical expressions but critical to achieving maximum efficiency. As an example of the method, the paper describes the optimization of the well-known CS-CG noise-cancelling LNA in 65-nm standard CMOS technology. Final post-layout simulations report very competitive results with a 3.7-dB noise figure, a 17-dB gain, and a cut-off frequency above 7 GHz.

Idioma: Inglés

DOI: 10.1109/ACCESS.2022.3158356

Año: 2022

Publicado en: IEEE Access 10 (2022), 29482-29492
ISSN: 2169-3536

Factor impacto JCR: 3.9 (2022)

Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 73 / 158 = 0.462 (2022) - Q2 - T2
Categ. JCR: TELECOMMUNICATIONS rank: 41 / 88 = 0.466 (2022) - Q2 - T2
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 100 / 274 = 0.365 (2022) - Q2 - T2

Factor impacto CITESCORE: 9.0 - Engineering (Q1) - Computer Science (Q1) - Materials Science (Q1)

Factor impacto SCIMAGO: 0.926 - Computer Science (miscellaneous) (Q1) - Materials Science (miscellaneous) (Q1) - Engineering (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/AEI/PID2020-114110RA-I00
Financiación: info:eu-repo/grantAgreement/ES/MINECO-FEDER/TEC2017-85867-R

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Electrónica (Dpto. Ingeniería Electrón.Com.)