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Robust and Reliable Modulation Classification for MIMO Systems |
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PP: 2513-2519 |
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Author(s) |
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Mohammad Rida Bahloul,
Mohd Zuki Yusoff,
M. Naufal M. Saad,
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Abstract |
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| This paper develops a feature-based Automatic Modulation Classification (AMC) algorithm for spatially multiplexed
Multiple-Input Multiple-Output (MIMO) systems. The proposed algorithm employs two Higher Order Cumulants (HOCs) of the
estimated transmit signal streams as discriminating features, and a multiclass Support VectorMachine (SVM) as a classification system.
A multi-classifier classification system is introduced to improve the robustness of the decision made by the classifier at each estimated
transmit signal stream. Furthermore, an optimal decision fusion scheme using aMaximum-Likelihood (ML) criterion is also introduced
to improve the accuracy and reliability of the final classification decision made in the fusion center. The proposed algorithm shows good
performance under different operating conditions, over an acceptable range of SNR, without any prior information about the channel
state. |
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