Automatic Modulation Recognition in Cognitive Radio Receivers using Multi-Order Cumulants and Decision Trees
M.Venkata Subbarao1, P.Samundiswary2
1M. Venkata Subbarao, Research Scholar, Department of Electronics Engineering, School of Engineering & Technology, Pondicherry University, Pondicherry, India.
2P. Samundiswary, 2Assistant Professor, Department of Electronics Engineering, School of Engineering & Technology, Pondicherry University, Pondicherry, India.
Manuscript received on 24 September 2018 | Revised Manuscript received on 30 September 2018 | Manuscript published on 30 November 2018 | PP: 61-69 | Volume-7 Issue-4, November 2018 | Retrieval Number: E1802017519©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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
Keywords: Modulation Classification, Cognitive Radio, Moments, Cumulants, Binary Trees
Scope of the Article: Classification