MATLAB Implementation of Predistortion Models

Predistortion technology is a crucial method in wireless communication systems for compensating nonlinear distortion in power amplifiers. By applying inverse distortion characteristics to the input signal in advance, it effectively enhances system linearity.

In MATLAB-implemented predistortion models, several key modules are typically included: First, the signal generation module produces baseband test signals using functions like randi for random symbol generation or qammod for modulation. Second, the predistorter module constructs nonlinear characteristics using polynomial methods (implemented via polyval) or lookup table approaches with interpolation functions like interp1. Third, the power amplifier model simulates real-device nonlinear behavior using memory polynomial models or Saleh models. Finally, the performance evaluation module employs metrics such as Error Vector Magnitude (EVM) calculated through comm.EVM measurements.

Delay estimation algorithms play a critical role in this implementation. Since signal transmission paths between the predistorter and power amplifier may introduce time delays, accurate compensation ensures precise alignment between the predistortion model and amplifier characteristics. Common delay estimation methods include cross-correlation algorithms (implemented using xcorr function) and peak detection techniques using findpeaks, which can be efficiently coded in MATLAB through built-in functions or custom scripts.

The typical processing flow of this MATLAB program involves: First, performing delay calibration on input-output signals using correlation-based alignment. Second, extracting predistorter parameters through optimization techniques like least squares method (lsqnonlin or backslash operator for linear systems). Finally, constructing a complete predistortion system model. This implementation approach serves both simulation studies and provides parameter configuration references for actual hardware deployment, with modular coding allowing separate testing of each component.