An Investigation of Wavelet Packet Transform for Spectrum Estimation

TL;DR

This paper explores wavelet packet transform as a flexible and effective method for spectrum estimation, demonstrating comparable or superior performance to traditional Fourier-based techniques.

Contribution

It introduces wavelet packet transform as a novel spectrum sensing approach with advantages in flexibility, reconfigurability, and adaptability.

Findings

Wavelet packet transform provides comparable or better spectral estimates.

The approach offers improved flexibility and reconfigure ability.

Performance metrics such as frequency resolution and variance are favorably impacted.

Abstract

In this article, we investigate the application of wavelet packet transform as a novel spectrum sensing approach. The main attraction for wavelet packets is the tradeoffs they offer in terms of satisfying various performance metrics such as frequency resolution, variance of the estimated power spectral density (PSD) and complexity. The results of the experiments show that the wavelet based approach offers great flexibility, reconfigure ability and adaptability apart from its performances which are comparable and at times even better than Fourier based estimates.