Journal ArticleDOI
Real-time Modulation Classification Based On Maximum Likelihood
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This paper converts an unknown signal symbol to an address of the look-up table (LUT), loads the pre-calculated values of the test functions for the likelihood ratio test, and produces the estimated modulation scheme in real-time.Abstract:
This paper describes a likelihood test based modulation classification method for identifying the modulation scheme of a software-defined radio (SDR) in real-time without pilot symbols between transmitters and receivers. Unlike the prior art, the paper converts an unknown signal symbol to an address of the look-up table (LUT), loads the pre-calculated values of the test functions for the likelihood ratio test, and produces the estimated modulation scheme in real-time. The statistical performance of the LUT based classifier is studied. Simulation results are presented to confirm the theoretical analysis.read more
Citations
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Journal ArticleDOI
Likelihood-Ratio Approaches to Automatic Modulation Classification
TL;DR: This survey paper focuses on the automatic modulation classification methods based on likelihood functions, studies various classification solutions derived from likelihood ratio test, and discusses the detailed characteristics associated with all major algorithms.
Journal ArticleDOI
Modulation format identification in heterogeneous fiber-optic networks using artificial neural networks.
TL;DR: Results of numerical simulations demonstrate that the proposed technique can effectively classify all these widely-used modulation formats with an overall estimation accuracy of 99.6% and also in the presence of various link impairments.
Journal ArticleDOI
Software-Defined Radio Equipped With Rapid Modulation Recognition
TL;DR: A discrete likelihood-ratio test (DLRT)-based rapid-estimation approach to identifying the modulation schemes blindly for uninterrupted data demodulation in real time is described and the statistical performance of the fast AMR associated with its implementation using the SDR is presented.
Journal ArticleDOI
Signal Identification for Multiple-Antenna Wireless Systems: Achievements and Challenges
TL;DR: The aim of this work is to provide a comprehensive state-of-the-art survey on algorithms proposed for the new and challenging signal identification problems specific to MIMO systems, including space-time block code (STBC) identification, MIMo modulation identification, and detection of the number of transmit antennas.
Journal ArticleDOI
Automatic modulation recognition using wavelet transform and neural networks in wireless systems
TL;DR: The proposed algorithm for automatic digital modulation recognition is verified using higher-order statistical moments (HOM) of continuous wavelet transform (CWT) as a features set and a multilayer feed-forward neural network trained with resilient backpropagation learning algorithm is proposed as a classifier.
References
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Journal ArticleDOI
Survey of automatic modulation classification techniques: classical approaches and new trends
TL;DR: The authors provide a comprehensive survey of different modulation recognition techniques in a systematic way, and simulated some major techniques under the same conditions, which allows a fair comparison among different methodologies.
Journal ArticleDOI
A comparison of SNR estimation techniques for the AWGN channel
D.R. Pauluzzi,Norman C. Beaulieu +1 more
TL;DR: The performances of several signal-to noise ratio (SNR) estimation techniques reported in the literature are compared to identify the "best" estimator and some known estimator structures are modified to perform better on the channel of interest.
Proceedings ArticleDOI
Likelihood ratio tests for modulation classification
TL;DR: Simulation results show that two novel modulation classification algorithms that are based on the decision theoretic approach can offer a significant performance gain for classification of dense, non-constant envelope constellations.
Journal ArticleDOI
A Study of Rough Amplitude Quantization by Means of Nyquist Sampling Theory
TL;DR: A simple picture of quantization noise permits an understanding of round-off error and its propagation in numerical solution, and of the effects of analog-to-digital conversion in closed-loop control systems.
Proceedings ArticleDOI
A new maximum-likelihood method for modulation classification
Wen Wei,Jerry M. Mendel +1 more
TL;DR: In this paper, a new maximum-likelihood method for modulation classification of digital amplitude-phase modulations, applicable to any constellation-based modulation types in an AWGN environment, is presented.
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