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Automatic Modulation Recognition Based on Morphological Operations

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Abstract

Automatic modulation recognition under negative signal-to-noise ratio (SNR) environment is a challenging topic. In this paper, we propose the method consisting of two main steps: constructing a template library and recognition. The former extracts the morphological envelope of each signal power spectrum by using the morphological close–open operation to construct the template library. The latter can further be divided into two sub steps. The first sub-step is to calculate the similarities between the morphological envelope of received signal power spectrum and each template in the template library. The second one is to determine the modulation type of received signal based on the maximum of the similarities which are more than the threshold. Simulation results demonstrate that the correct recognition rate (CRR) can increase by 0.84 % and 9.38 % with hierarchical method and ZAM-GTFR method at SNR=−4 dB, respectively. The proposed method can reduce the computational complexity by about 97 % compared with the ZAM-GTFR method when N≤4096. The results prove the method has the advantage of high CRR and the less computation.

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Authors and Affiliations

  1. School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin, 300384, China

    Yuan Zhang, Xiurong Ma & Duo Cao

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  1. Yuan Zhang
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  2. Xiurong Ma
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  3. Duo Cao
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Correspondence to Yuan Zhang.

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Zhang, Y., Ma, X. & Cao, D. Automatic Modulation Recognition Based on Morphological Operations. Circuits Syst Signal Process 32, 2517–2525 (2013). https://doi.org/10.1007/s00034-013-9577-4

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  • DOI: https://doi.org/10.1007/s00034-013-9577-4

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