Nonlinear Analysis of the Diode-Connected Transistor Mixers Using Volterra Series: Generalized Matrix Approach in the Frequency Domain

The article is a sequel to the research devoted to the frequency mixers analysis based on generalized matrix approach in the frequency domain. This research investigates the nonlinear characteristics of diode-connected transistor mixers through the application of Volterra series, specifically balanced, double balanced, and triple balanced mixer configurations. An analytical algorithm is proposed to assess the nonlinear distortion caused by the third harmonic. The results encompass both theoretical calculations and simulations performed in Cadence Design Systems.

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Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1109/eexpolytech62224.2024.10755550
Citations
1
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.36

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article

Nonlinear Analysis of the Diode-Connected Transistor Mixers Using Volterra Series: Generalized Matrix Approach in the Frequency Domain

Alexander S. Korotkov, Olga A. Golovan
1 citations
Matrix Theory and Algorithms
0.36
article

Nonlinear Analysis of the Diode-Connected Transistor Mixers Using Volterra Series: Generalized Matrix Approach in the Frequency Domain

Alexander S. Korotkov, Olga A. Golovan
article en
1 citations

Abstract

The article is a sequel to the research devoted to the frequency mixers analysis based on generalized matrix approach in the frequency domain. This research investigates the nonlinear characteristics of diode-connected transistor mixers through the application of Volterra series, specifically balanced, double balanced, and triple balanced mixer configurations. An analytical algorithm is proposed to assess the nonlinear distortion caused by the third harmonic. The results encompass both theoretical calculations and simulations performed in Cadence Design Systems.

Peter the Great St. Petersburg Polytechnic University (RU)
Russian Science Foundation
Affordable and clean energy
Openalex Percentile: Top 34%
Matrix Theory and Algorithms
0.36
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