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Abstract
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Article Information:
Efficient and Low Complexity Modulation Classification Algorithm for MIMO Systems
Mohammad Rida Bahloul, Mohd Zuki Yusoff and M. Naufal M. Saad
Corresponding Author: Mohammad Rida Bahloul
Submitted: July 14, 2014
Accepted: August 26, 2014
Published: January 05, 2015 |
Abstract:
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This study develops a feature-based Automatic Modulation Classification (AMC) algorithm for spatially multiplexed Multiple-Input Multiple-Output (MIMO) systems employing two Higher Order Cumulants (HOCs) of the estimated transmit signal streams as discriminating features and a multiclass Support Vector Machine (SVM) as a classification system. The algorithm under study has the capability to recognize a wide range of modulation schemes without any prior information about the channel state. The classification performance of the proposed algorithm was evaluated via extensive simulations under different operating conditions and was also compared with the one obtained with the optimal Hybrid Likelihood Ratio Test (HLRT) approach. The results show that the proposed algorithm is capable of classifying the considered modulation schemes with good classification accuracy and can achieve performance comparable to that of the HLRT approach while having a significantly lower computational complexity.
Key words: Automatic modulation classification, higher-order cumulants, multiple-input multiple-output, support vector machine, , ,
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Cite this Reference:
Mohammad Rida Bahloul, Mohd Zuki Yusoff and M. Naufal M. Saad, . Efficient and Low Complexity Modulation Classification Algorithm for MIMO Systems. Research Journal of Applied Sciences, Engineering and Technology, (1): 58-64.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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