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Blind Digital Modulation Identification Using an Efficient Method-of-Moments Estimator

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Abstract

The automatic identification of the modulation format of a detected signal is a major task of an intelligent receiver in both military and civilian applications. It is well known that the maximum likelihood (ML) classifier requires a priori knowledge of the incoming signal and channel (including amplitude, timing information, noise power, and the roll-off factor of the pulse-shaping filter). To relax this requirement, we introduce a novel estimator to estimate the parameters required by the ML classifier which is blind to the modulation scheme of the received signal, and this gives rise to a new blind modulation classifier for digital amplitude-phase modulated signals. While the proposed classifier is completely blind, the simulation results show that the performance of this classifier is very close to the optimal non-blind classifier.

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Notes

  1. In this paper, we assume a block fading channel in which the channel amplitude and phase are constant over the N symbol observation interval.

  2. ∑ +∞k=−∞ x(t − kT) = (1/T) ∑ +∞k=−∞ X(k/T) exp (j2πkt/T), where X(f) is the Fourier transform of a function x(t).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Babol University of Technology, Babol, 47148-71167, Iran

    Hamid Amiri Ara, M. R. Zahabi & Ataollah Ebrahimzadeh

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  1. Hamid Amiri Ara
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  2. M. R. Zahabi
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  3. Ataollah Ebrahimzadeh
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Correspondence to Hamid Amiri Ara.

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Amiri Ara, H., Zahabi, M.R. & Ebrahimzadeh, A. Blind Digital Modulation Identification Using an Efficient Method-of-Moments Estimator. Wireless Pers Commun 116, 301–310 (2021). https://doi.org/10.1007/s11277-020-07715-2

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