Neural networks (NNs) are becoming an increasingly attractive solution for power amplifier
(PA) behavioral modeling, due to their excellent approximation capability. Recently, different …

To reduce power consumption of wireless transmitters, the transmission power level of RF
power amplifiers (PAs) may dynamically change according to real-time data traffic. This …

This paper presents a study of performance evaluation metrics for behavioral models of
power amplifiers and transmitters. A novel normalized absolute mean spectrum error …

This paper reports an adaptive digital predistorter (DPD) with fast convergence rate and low
complexity for multi-channel transmitters, which is fully implemented in a field programmable …

A deep learning-based M-ary spread spectrum (SS) underwater acoustic (UWA)
communication system is proposed. The long short-term memory (LSTM) model is used as …

In this paper, a study of the power alignment issue in digital predistorters is presented. The
proper alignment is achieved by adjusting the normalization gain used to synthesize the …

Power amplifiers are widely used in RF broadcasting applications. However, they tend to
exhibit nonlinear behavior that distorts the input signals both in the time and frequency …

Traditionally, power amplifier behavioral modeling and digital predistortion have been
based on polynomials or Volterra series. Recently, however, there has been a trend to …

Distributed base station architectures represent the new trend that operators follow in order
to resolve cost, performance and efficiency challenges when deploying 4G networks. Main …

In this paper, an efficient Dice coefficient matching-based sparsity adaptive matching pursuit
(DSAMP) algorithm is introduced to prune the redundant terms of power amplifier (PA) …