Automatic modulation recognition in cognitive radio receivers using multi-order cumulants and decision trees

Abstract

Design of intelligent receiver is a major footstep in the implementation of Cognitive Radio (CR). Automatic Modulation Recognition (AMR) of the received signal decides the performance of the intelligent receiver. This paper proposes new classification algorithms for AMR using supervised Decision Tree (DT). DT Classifiers (DTC’s) are non-parametric classifiers which provide high speed and low complex solutions in classification. Fine Tree (FT), Medium Tree (MT) and Coarse Tree (CT) classifiers are implemented in this paper which is trained with multi-order cumulants to achieve optimum classification accuracy. Performance of DTC’s is compared with other classifiers stated in literature to prove their superiority in modulation classification.