Generalized Two-Box Cascaded Nonlinear Behavioral Model for Radio Frequency Power Amplifiers With Strong Memory Effects

Accurately modeling the memory effects is critical in modeling and nonlinearity pre-compensation for wideband radio frequency (RF) power amplifiers (PAs) with strong memory effects. In this paper, the memory effects are divided into two categories: lagging memory effect and leading memory effect, which are defined based on the input samples located after and before the current output samples, separately. Considering the above two types of memory effects, a generalized two-box cascaded (GTBC) nonlinear behavioral model for RF PAs with strong memory effects is proposed: one box for a static nonlinearity block that is used to include the strong static nonlinearities and the other box for a dynamic nonlinearity block which is used to predict the mild dynamic nonlinearities. The modeling accuracy of the proposed model, in terms of the normalized mean square error (NMSE) and the memory effect intensity (MEI), is compared to the generalized memory polynomial (GMP), the augmented Hammerstein (AH) and the enhanced Hammerstein (EH) models for a 450-470 MHz Doherty PA with a three-carrier WCMDA input signal and a 895-935 MHz inverse Class-F Doherty PA with a single-carrier FDD-LTE OFDM input signal. The validation demonstrates that the proposed model leads to high-accuracy with fewer modeling coefficients and floating point operations (FLOPs).