The wavelet packet transform and peak typed Markov chain can be used to model the colored background noise for low-voltage power line channels. Different wavelet basis functions have a major impact on the accuracy of noise modeling. Under different wavelet basis functions, the simulated colored background noise is modeled by wavelet packet transform and peak typed Markov chain respectively, and their power spectrum densities before and after modeling are calculated as well as their corresponding root-mean-square errors (RMSE). In the aspect of modeling accuracy, it can be found that the Daubecies wavelet is the best and the Haar wavelet followed. Therefore, the Daubecies wavelet is the best wavelet basis function ofthe wavelet packet transform and peak typed Markov chain, which can be used to model the colored background noise in low-voltage power line channels.