Large and small signal distortion analysis using modified Volterra series

Abstract

A new approach to the Volterra analysis of analog circuits is presented. Volterra analysis is widely used for the calculation of harmonic and intermodulation distortion products. However, the analysis is limited to circuits experiencing small signal excitations and becomes inaccurate when the input signal amplitude increases, especially when MOS transistors are involved. In this paper, we analyze the cause of this drawback, which is no other than the Taylor series' convergence properties. Moreover, we propose a solution, by calculating the nonlinearity coefficients using a different type of polynomial expansion, the Chebyshev series. This replacement improves significantly the capabilities of Volterra analysis. We also present results comparing Chebyshev series with other types of polynomial expansions. Finally, we apply the proposed method to analyze the intermodulation distortion (IMD) of a CMOS RF power amplifier, both in the small and the large signal regimes.

High frequency CMOS amplifier with improved linearity

“…Future work include using more accurate non‐linear analysis such as Monte‐Carlo method, etc. [26] and optimising the power efficiency and other critical parameters for RF/microwave applications. Also, in order to further improve the overall system performance, a detailed investigation of the non‐linear feedback system in the technique could be carried out.…”

“…3a. As can be seen, when the value of R ′ G in (25), (26) and (27) is replaced by R G // R N , R ′ G + R F = 0, which will result in HD 2f | with =0, HD 3f | with = 0 and IMD 3f | with = 0. That is: theoretically, the second and third-order harmonic distortion as well as the IMD can be cancelled with the compensation technique.…”

Estimating Scattering Potentials in Inverse Problems with a Non-Causal Volterra Model

“…This method has its advantages; however, due to the simple non-orthogonal polynomial basis, it also has its drawbacks when one wants to estimate a high number of kernels with this method. To overcome the numerical problems that usually plauge the simple polynomial expansions [38], Equation (3) can be rewritten in an orthogonal polynomial basis using, e.g., Chebyshev polynomials [39]. Another identification method is the frequency domain approach, where the kernels are identified in the frequency space after Fourier transformation [40].…”

Distortion Contribution Analysis for Identifying EM Immunity Failures

“…A problem with this approach is the difficulty of determining the higher-order derivatives [10]. Additionally, the Taylor series suffers from a limited convergence radius, especially for transistors biased close to operating region boundaries [20]. To solve these issues, we fit the polynomial models from simulated I-V data using a least squares approximation [25].…”