Basic Predistortion code for Saleh and Rapp nonlinearity

I want to find a way to easily predistort the input of a power amplifier in MATLAB. The amplifier is modeled as a Saleh or Rapp nonlinearity using the communications toolbox. I have tried the digital predistorter (https://www.mathworks.com/help/comm/ref/comm.dpd-system-object.html), but when I feed the result into my Rapp or Saleh amplifier, the output looks very nonlinear. I thought this would be an easy thing to do.

Later, I want to expand this approach to a real power amplifier designed in Cadence.

Answer 1

[Maneet Kaur Bagga]

Hi,

As per my understanding, you are using MATLAB's "comm.DPD" system object but you observed that the output of your amplifier remains highly nonlinear. This suggests that either:

1. The chosen predistortion method does not match the amplifier's characteristics.
2. The predistorter is not trained adequately for the specific amplifier model.

Please refer to the following steps to resolve the issue:

Model Matching: Ensure the predistorter matches the nonlinearity model of the amplifier. For Rapp and Saleh models:

• Rapp model introduces AM-AM distortion (soft compression) with a parameter controlling the transition sharpness.
• Saleh model introduces both AM-AM and AM-PM distortions.

Train the Predistorter for Adaptive Correction: Use the "comm.DPD" object, implement a feedback loop to iteratively correct errors. Please refer to the following code snippet:

dpd = comm.DPD('MemoryOrder', 3, 'PolynomialOrder', 5);
release(dpd); % Allow reconfiguration
dpd.Weights = [initial_guess]; % Initialize weights

% Adaptive training loop
for iteration = 1:maxIterations
    x_predistorted = dpd(x_input);
    y_amplified = amplifier(x_predistorted);
    error = desired_output - y_amplified;
    dpd = adaptDPD(dpd, error, learningRate);
end

Once the predistortion works for your Saleh/Rapp models, you can export data from Cadence (input-output samples of the amplifier). Repeat the predistortion process.

Hope this helps!