Skip to content

jankralx/dpd_sample_selection

Repository files navigation

Feedback Sample Selection Methods Allowing Lightweight Digital Predistorter Adaptation

The Matlab source codes are provided to supplement our research paper "Feedback Sample Selection Methods Allowing Lightweight Digital Predistorter Adaptation". They allows to reproduce simulation results in our paper.

Requirements

We have run simulations on Ubuntu OS, Matlab 2018a, but the simulations should be OS independent and all Matlab versions > 2018 should be compatible. Please note that for faster simulation executation Distributed Computation Toolbox is required, however, all simulations can be executed without parfor loops and hence should require no toolboxes.

Simulation Execution

The source codes are split into two parts: 1) calculation of results, 2) generating plots.

  1. run RUN_ANALYSIS_04.m to generate simulation results
  2. run PLOT_RESULTS_04.m to plot the simulation results

Please note that simulations are quite time demanding and can execute more than 24 hours (depending on the performance of HW).

Extended Simulations

By default, Matlab script RUN_ANALYSIS_04.m loads already optimised histograms from results_01_hist.mat. You can turn on histogram optimisation by changing the line 15 of RUN_ANALYSIS_04.m to "pars.is_hist_training = 1;".

Please Cite Our Paper

About

Digital predistortion with sample selection methods.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages