This paper presents a robust signal classification scheme for achieving comprehensive spectrum sensing of multiple coexisting wireless systems. It is built upon a group of feature-based signal detection algorithms enhanced by the proposed dimension cancelation (DIC) method for mitigating the noise uncertainty problem. The classification scheme is implemented on our testbed consisting real-world wireless devices. The simulation and experimental performances agree with each other well and shows the effectiveness and robustness of the proposed scheme.
@article{arxiv.1207.5342,
title = {A Robust Signal Classification Scheme for Cognitive Radio},
author = {Hanwen Cao and Jürgen Peissig},
journal= {arXiv preprint arXiv:1207.5342},
year = {2016}
}