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This is the Matlab code for the paper "Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems" published in the IEEE Wireless Communications Letters.

Home Page: https://doi.org/10.1109/LWC.2020.2969157

License: MIT License

MATLAB 100.00%
wireless-communications denoising-features ieee digital-modulation-identification modulation-recognition modulation-classification modulation cognitive-radio higher-order-statistics mimo

denoising-hom-for-dmi's Introduction

Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems

License

Copyright (C) 2020 Sofiane Kharbech, Eric Pierre Simon, Akram Belazi, and Wei Xiang.

This software is under the MIT License.

Paper citation

S. Kharbech, E. P. Simon, A. Belazi and W. Xiang, "Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems," in IEEE Wireless Communications Letters, vol. 9, no. 6, pp. 765-769, June 2020.

Main scripts

  • GenDataset.m: generates a set of HOM that allows identifying the modulation type. In this file, you can edit all the transmitter, channel, and receiver parameters.
  • DetectionResults.m: shows the detection performance, i.e., the probability of correct identification in terms of the SNR.

Fonction scripts

  • f_HOS_Extraction.m: includes the following processes: source signals generation, channel mixing, blind source separation (BSS), and features extraction.
  • f_CalcHOS.m: given a signal x, this function estimates HOC and both denoised and non-denoised HOM.
  • f_SCMA.m: is the function that performs the BSS process following the SCMA algorithm.

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