We propose an over-the-air digital predistortion optimization algorithm using reinforcement
learning. Based on a symbol-based criterion, the algorithm minimizes the errors between …

A novel undersampled feedback signal iterative learning control (US-ILC-DPD) technique is
proposed to linearize RF power amplifiers (PAs). The proposed method combines the …

This paper proposes an efficient neural-network-based digital predistortion (DPD), named
as envelope time-delay neural network (ETDNN) DPD. The method complies with the …

This paper provides an extended analysis of the adaptive digital predistortion technique
initially proposed and conceptually overviewed in. This digital predistortion technique is …

In this paper, a robust and broadband digital predistortion (DPD) based on negative
feedback iteration technique is proposed for linearization of power amplifier with strong …

A novel digital predistortion (DPD) with an ultralow feedback sampling rate is proposed for
wideband wireless communications. Analytical groundwork is carried out to support the …

In this paper, a low-feedback-sampling-rate digital predistortion (DPD) method is proposed
for wideband wireless transmitters and radio-frequency power amplifiers (PAs). This DPD …

In this paper, we present a novel digital predistortion (DPD) solution based on a direct
learning approach, which is capable of reducing the unwanted emissions resulting from the …

Highly-efficient operation of communication systems requires effective compensation of
nonlinear distortion with memory. The main contributor to nonlinearity is the high-power …

The impact of feedback noise on digital predistortion with intuitive direct learning is
investigated. The noise leads to an extra NMSE, which is NMSE η= 1/Gp (1-| 1-θ| 2). σ n 2/P …