Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
The Volterra and Wiener Theories of Nonlinear Systems
The Volterra and Wiener Theories of Nonlinear Systems
Orthogonal Neural Network Based Predistortion for OFDM Systems
CERMA '07 Proceedings of the Electronics, Robotics and Automotive Mechanics Conference
A Generalized Memory Polynomial Model for Digital Predistortion of RF Power Amplifiers
IEEE Transactions on Signal Processing
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To predistort a power amplifier's nonlinearity with memory effects, various predistorters with memory are proposed. Among them, the memory polynomial (MP)-based predistorter attracts more attentions due to its low complexity and good performance. The nonlinearity order and memory order, as two key parameters of a MP-based predistorter, have great effect on the linearization performance. In this paper, a low complexity order-decision approach is proposed to find the optimal nonlinearity and memory order for MP-based predistorters. The proposed approach can make a predistorter fit for different PAs. This makes a predistorter more intelligent and universal. Finally, the proposed approach is verified by simulations and experiments.