Covers theoretical and practical aspects related to the behavioral modelling and
predistortion of wireless transmitters and power amplifiers. It includes simulation software …

A comparative study of nonlinear behavioral models with memory for radio-frequency power
amplifier (PAs) is presented. The models are static polynomial, parallel Hammerstein (PH) …

A radial-basis function neural network (RBFNN) has been used for modeling the dynamic
nonlinear behavior of an RF power amplifier for third generation. In the model, the signal's …

A new, dynamic behavioral modeling technique, based on a time-delay support vector
regression (SVR) method, is presented in this paper. As an advanced machine learning …

The objective of this paper is to present an approach to behavioral modeling that can be
applied to predict the nonlinear response of power amplifiers with memory. Starting with the …

In this paper different evaluation criteria for power amplifier behavioral modeling are studied
and evaluated using measuremed data. The figure-of-merits are calculated from complex …

This chapter is devoted to the use of machine learning (ML) algorithms in digital front‐end
(DFE) with the emphasis on crest factor reduction techniques, digital predistortion (DPD) …

In this paper, we present an envelope-domain behavioral model of a high-power RF
amplifier. In this modeling approach, we use the signal envelope information, and the …

This paper explains the nonlinear dynamic memory effects observed on both AM-AM and
AM-PM conversions of nonlinear microwave power amplifier, PA, circuits. The study is …

In this article, a recurrent neural network (RNN) method is employed for dynamic time‐
domain modeling of both linear and nonlinear microwave circuits. An automated RNN …