Robust automatic modulation classification and blind equalization: novel cognitive receivers

Abstract

The automatic modulation classifier (AMC) is an important signal processing component that helps the cognitive radio (CR) better utilize the spectrum. In a typical CR scenario, training sequence or channel knowledge is not available, and hence blind equalizers are widely used. The multipath fading channel not only affects symbol detection performance but also affects the performance of the AMC. In a conventional single input single output blind equalizer, the weights of the equalizer are adapted by minimizing cost functions that are non quadratic (multimodal).

Combined Blind Equalization and Classification of Multiple Signals

“…The first work is in (Wu and Wu, 2008), where a robust switching SISO blind equalizer is proposed that improves the performance of single user AMC. In the second work (Ramkumar and Bose, 2010a), the weights of the SISO blind equalizer are adapted in such a way that performance of the cumulants based single user is improved.…”

“…In this paper we propose a MIMO blind equalizer that improves the performance of both multiuser symbol detection and MAMC that was proposed in (Ramkumar and Bose, 2010a). In order to do so, we design a cost function that is related to the performance of the multiuser AMC and then choose the parameters of the blind equalizer such that the cost function is maximized.…”