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automatic modulation format/bit-rate classification and signal-to-noise ratio estimation using asynchronous delay-tap sampling

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COMPUTERS & ELECTRICAL ENGINEERING 2015年 47卷 126-133页

作者： Khan, Faisal Nadeem Teow, Chiew Hoon Kiu, Shiu Guong Tan, Ming Chieng Zhou, Yudi Al-Arashi, Waled Hussein Lau, Alan Pak Tao Lu, Chao Hong Kong Polytech Univ Dept Elect Engn Kowloon Hong Kong Peoples R China Univ Sains Malaysia Sch Elect & Elect Engn George Town Malaysia Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur Malaysia Texas A&M Univ Dept Elect & Comp Engn College Stn TX USA Univ Sci & Technol Dept Elect Engn Sanaa Yemen Hong Kong Polytech Univ Dept Elect & Informat Engn Kowloon Hong Kong Peoples R China

We propose a novel technique for automatic classification of modulation formats/bit-rates of digitally modulated signals as well as non-data-aided (NDA) estimation of signal-to-noise ratio (SNR) in wireless networks. The proposed technique exploits modulation format, bit-rate, and SNR sensitive features of asynchronous delay-tap plots (ADTPs) for the joint estimation of these parameters. Simulation results validate successful classification of three commonly-used modulation formats at two different bit-rates with an overall accuracy of 99.12%. Similarly, in-service estimation of SNR in the range of 0-30 dB is demonstrated with mean estimation error of 0.88 dB. The proposed technique requires low-speed asynchronous sampling of signal envelope and hence, it can enable simple and cost-effective joint modulation format/bit-rate classification and NDA SNR estimation in future wireless networks. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： automatic modulation classification automatic modulation format and bit-rate classification SNR estimation Asynchronous delay-tap sampling

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Hybrid Maximum Likelihood modulation classification for Continuous Phase modulations

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IEEE COMMUNICATIONS LETTERS 2016年第3期20卷 450-453页

作者： Yuan, Yabo Zhao, Peng Wang, Bo Wu, Bin Beijing Inst Tracking & Telecommun Technol Beijing 100094 Peoples R China Key Lab Space Object Measurement Beijing 100094 Peoples R China

In this letter, we propose a hybrid maximum likelihood (HML) classifier for continuous phase modulation (CPM). To the best of our knowledge, the proposed likelihood function is the first one for CPM signals that is based on two of its main features: nonlinear waveform, which is represented with its principal components, and signal memory, which is modeled as a Markov mapping symbol sequence. Unknown channel parameters are estimated through the expectation-maximization (EM) algorithm. An approximation method is further proposed to ensure that the proposed classifier improves classification performance at the cost of a moderate increase in calculations. Numerical results prove the superiority of the proposed approach over the classical HML classifier and feature-based classifier in terms of classifying CPM and linear modulation.

关键词： automatic modulation classification CPM ML estimation EM algorithm principal component analysis

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Joint modulation classification and Antenna Number Detection for MIMO Systems

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IEEE COMMUNICATIONS LETTERS 2016年第1期20卷 193-196页

作者： Turan, Merve Oner, Menguc Cirpan, Hakan Ali Istanbul Tech Univ Dept Elect & Commun Engn TR-80626 Istanbul Turkey Isik Univ Dept Elect & Elect Engn Istanbul Turkey

Noncooperative classification of the modulation type of communication signals finds application in both civilian and military contexts. Existing modulation classification methods for multiple-input multiple-output (MIMO) communication systems commonly require a priori information on the number of transmit antennas employed by the multiantenna transmitter, which, in most of the noncooperative scenarios involving modulation classification, is unknown and needs to be blindly extracted from the received signal. Since the problems of MIMO modulation classification and detection of the number of transmit antennas are highly coupled, we propose a decision theoretic approach for spatial multiplexing MIMO systems that considers these two tasks as a joint multiple hypothesis testing problem. The proposed method exhibits a high performance even in moderate to low SNR regimes while requiring no a priori knowledge of the channel state information and the noise variance.

关键词： automatic modulation classification multipleinput multiple-output minimum description length

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The Performance of Feature-Based classification of Digital modulations under varying SNR and Fading Channel Conditions

The Performance of Feature-Based Classification of Digital M...

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IEEE AFRICON Conference - Science, Technology and Innovation for Africa

作者： Uys, L. Y. Gouws, M. Strydom, J. J. Helberg, A. S. J. NWU Sch Elect Elect & Comp Engn Potchefstroom South Africa CSIR DPSS Pretoria South Africa

ISBN: (纸本)9781538627754

Feature-based classification is a method used for automatic modulation classification of communication signals. This method requires extraction of various features from a signal. One of the approaches for feature extraction is the use of instantaneous amplitude, phase and frequency. The performance of these features under different SNR conditions is well described in literature [1] - [2], but the effect of fading on the extracted features has received little investigation. In this paper we investigate the quality of the features in a static multipath Rayleigh fading channel under varying channel conditions. It was found that most feature values are distinguishable for the different digital signals in a flat fading channel. This work shows the behaviour of these features in a fading channel under deteriorating conditions and suggests ways to reduce the effect of the fading on the classification of the signals.

关键词： automatic modulation classification feature based classification feature extraction Rayleigh fading flat fading

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Novel Hierarchical Tag-Recognition for RFID Systems

Novel Hierarchical Tag-Recognition for RFID Systems

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IEEE Global Telecommunications Conference (GLOBECOM)

作者： Pu, Limeng Wu, Hsiao-Chun Yan, Kun Louisiana State Univ Sch Elect Engn & Comp Sci Baton Rouge LA 70803 USA Guilin Univ Elect Technol Dept Informat & Telecommun Guilin 541004 Peoples R China

ISBN: (纸本)9781509050192

In this paper, we propose a new hierarchical radio-frequency identification (RFID) tag-recognition method based on the graph-based automatic modulation classification (AMC) and direct-sequence spread-spectrum (DSSS). In our proposed method, RFID tags can be modulated using different modulation schemes according to different scenarios (e.g., different users or different devices). For each modulation scheme, the direct-sequence spread-spectrum strategy is employed to allow simultaneous transmissions of multiple tags. In the first hierarchy, different modulation types are employed to distinguish different users, the graph-based AMC is built upon the periodicity of the modulated signals. The cyclic spectrum of the received signal is first established. The graph representation is then constructed according to the cyclic spectrum. Ultimately, robust features are extracted from the graph representation. In the second hierarchy, the DSSS scheme is utilized to differentiate the control or sensed data carried by individual tags, the signature sequence set with low cross-correlations is generated from Gold and Kasami sequences. In the third hierarchy, the information data sequences are thus spread by these signature sequences. In our proposed new RFID framework, multiple tags can transmit the signals simultaneously in the same frequency band where the dominant tag signal will be identified and its carried information can be recovered. Monte Carlo simulation results demonstrate the promising performance of our proposed new scheme.

关键词： Radio-frequency identification (RFID) automatic modulation classification cyclic spectrum direct-sequence spread-spectrum (DSSS)

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BLIND DIGITAL modulation classification BASED ON M-TH POWER NONLINEAR TRANSFORMATION

BLIND DIGITAL MODULATION CLASSIFICATION BASED ON M-TH POWER ...

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IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Gouldieff, Vincent Palicot, Jacques Daumont, Steredenn Cent Supelec IETR Ave Boulaie CS 47601 F-35576 Cesson Sevigne France Zodiac Data Syst 2 Rue Caen F-14740 Bretteville Lorgueilleus France

ISBN: (纸本)9781509045457

automatic modulation classification (AMC) has received a major attention last decades, as a required step between signal detection and demodulation. In the fully-blind scenario, this task turns out to be quite challenging, especially when the computational complexity and the robustness to uncertainty matter. AMC commonly relies on a preprocessor whose function is to estimate unknown parameters, filter the received signal and sample it in a suitable way. Any preprocessing error inherently leads to a performance loss. To improve the robustness of the blind AMC, we propose to proceed almost directly on the received signal - with neither matched-filtering step nor synchronization step. In this paper, Analytical Mth-Power nonlinear Transformation (AMPT) is considered for its robustness towards timing, phase and frequency uncertainty. The generated feature-vector then feeds a Minimum Distance classifier. Numerical simulations show the effectiveness of the proposed method for a 7-class problem of low-order modulations.

关键词： automatic modulation classification Mth-Power nonlinear Transform Blind Detection

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Multipath channel estimation algorithm for automatic modulation classification using sixth-order cumulants

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ELECTRONICS LETTERS 2010年第19期46卷 1348-1349页

作者： Orlic, V. D. Dukic, M. L. Inst Microwave Tech & Elect IMTEL Komunikacije AD Belgrade 11070 Serbia Univ Belgrade Fac Elect Engn Belgrade 11000 Serbia

An algorithm is described for estimation of multipath fading channels without a priori information on channel characteristics, for application in automatic modulation classification based on normalised sixth-order cumulants. Compared with existing approaches, the proposed algorithm can achieve much better classification accuracy in distinguishing complex-valued modulation techniques. Theoretical analysis is verified via extensive Monte-Carlo simulations.

关键词： Monte Carlo methods Monte-Carlo simulations automatic modulation classification channel estimation complex-valued modulation techniques fading channels modulation multipath channels multipath fading channel estimation algorithm normalised sixth-order cumulants

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Cumulants-based modulation classification technique in multipath fading channels

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IET COMMUNICATIONS 2015年第6期9卷 828-835页

作者： Chang, Dah-Chung Shih, Po-Kuan Natl Cent Univ Dept Commun Engn Taoyuan 32001 Taiwan

automatic modulation classification (AMC) is a classical topic in the signal classification field and is often performed when the modulation type is adaptive. For typical modulation types such as M-PSK and M-QAM, the fourth-order cumulant statistics are usually used for modulation classification. Besides, it is also known that the AMC performance can be seriously degraded by the effects of multipath fading in wireless channels when compared with the ideal white Gaussian noise channel. In this study, a new modulation classification method is proposed, exploring different features of normalised fourth-order cumulant statistics for a modified blind channel estimation method in the multipath fading channel. The relationship between the cumulants of the received signal and the multipath fading effects is established to cope with the channel impulse response in the new algorithm. Simulation results show that the performance of the proposed AMC method is much improved than that of previously proposed ones in terms of the probability of correct classification.

关键词： multipath channels fading channels higher order statistics phase shift keying quadrature amplitude modulation white noise Gaussian noise Gaussian channels channel estimation probability signal classification cumulant-based modulation classification technique multipath fading channels automatic modulation classification signal classification field modulation type M-PSK M-QAM AMC performance wireless channels ideal white Gaussian noise channel normalised fourth-order cumulant statistics modified blind channel estimation method received signal multipath fading effects channel impulse response AMC method correct-classification probability

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A Unified Practical Approach to modulation classification in Cognitive Radio using Likelihood-Based Techniques 28

A Unified Practical Approach to Modulation Classification in...

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IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Salam, Ahmed O. Abdul Sheriff, Ray E. Al-Araji, Saleh R. Mezher, Kahtan Nasir, Qassim Univ Bradford Sch Elect Engn & Comp Sci Bradford BD7 1DP W Yorkshire England Khalifa Univ Sci Technol & Res Sharjah U Arab Emirates Sharjah Univ Sharjah U Arab Emirates

ISBN: (纸本)9781479958290

The automatic classification of digital modulated signals has been subject to extensive studies over the last decade, with numerous scholarly articles and research studies published. This paper provides an insightful guidance and discussion on the most practical approaches of automatic modulation classification (AMC) in cognitive radio (CR) using likelihood based (LB) statistical tests. It also suggests a novel idea of storing the known constellation sets on the receiver side using a look-up table (LUT) to detect the transmitted replica. Relevant performance measures with simulated comparisons in flat fading additive white Gaussian noise (AWGN) channels are examined. Namely, the average likelihood ratio test (ALRT), generalized LRT (GLRT) and hybrid LRT (HLRT) are particularly illustrated using linearly phase-modulated signals such as M-ary phase shift keying (MPSK) and quadrature amplitude modulation (MQAM). When the unknown signal constellation is estimated using the maximum likelihood (ML) method, results indicate that the HLRT performs well and near optimal in most situations without extra computational burden.

关键词： cognitive radio automatic modulation classification likelihood algorithms

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automatic modulation classification Algorithm Using Higher-Order Cumulants Under Real-World Channel Conditions

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IEEE COMMUNICATIONS LETTERS 2009年第12期13卷 917-919页

作者： Orlic, Vladimir D. Dukic, Miroslav L. IMTEL Komunikacije Ad Inst Microwave Tech & Elect Belgrade 11070 Serbia Univ Belgrade Fac Elect Engn Belgrade 11001 Serbia

An automatic modulation classification algorithm for application in communications via multipath fading channels, without a priori information on channel characteristics, based on normalized sixth-order cumulants is described. In comparison with existing approaches, proposed algorithm can achieve much better classification accuracy in distinguishing BPSK from complex-valued modulation techniques. Theoretical analysis is verified via extensive simulations, under real-world channel propagation conditions.

关键词： automatic modulation classification cumulants channel modeling multipath channel

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