Behavioral modeling of nonlinear RF power amplifiers considering memory effects

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Wide-band dynamic modeling of power amplifiers using radial-basis function neural networks (2005, methodology): “Typical convergence curves of the training process are shown in Section IV.”
A comparative analysis of behavioral models for RF power amplifiers (2006, methodology): “Recently, methods using sparse delays [14] and pruned Volterra series [29] have been used for optimizing model performance .”
A New Digital Predictive Predistorter for Behavioral Power Amplifier Linearization (2007, methodology): “The most usual models employed for digital PD are: memory polynomials or nonlinear moving average (MA) models [2], [3], Hammerstein [4], [5], and Wiener [6], [7] models with their cascade and parallel variants and using finite or infinite impulse response (FIR or IIR) filters to model the”
Deembedding static nonlinearities and accurately identifying and modeling memory effects in wide-band RF transmitters (2005, positive): “Therefore, this modeling approach is robust, and it is independent of the PA technology and its operation class.”
Novel Index Modulation Techniques: A Survey (2019, background): “Owing to the IFFT at TX, OFDM signals suffer from high PAPR, which results in severe nonlinear distortions caused by the limited dynamic range and nonlinearities in the power amplifier for RF communications [74] or in the LED emitter for VLC [75].”