A study on the application of wavelet packet transforms to Cognitive Radio spectrum estimation

Spectrum sensing is an important functionality of cognitive radio (CR). Accuracy and speed of estimation are the key indicators to select the appropriate spectrum sensing technique. Conventional spectrum estimation techniques which are based on short time Fourier transform (STFT) suffer from familiar problems such as low frequency resolution, variance and high side lobes/leakages. In this article, the possibility of employing wavelet packet decomposition as a basis for new spectrum sensing approach is investigated. Three types of sources, namely partial band, single tone and swept tone, are used to investigate the performance of the proposed wavelet based approach. Swept tone source is a special kind of source devised to simulate the temporal dynamics in cognitive radio. The results of the experiments show that the wavelet based approach is quite promising for spectral estimation and can be a suitable technology for CR applications.