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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Wang, Fanggang Xu, Rongtao Zhong, Zhangdui Institute of Network Coding CUHK Hong Kong State Key Laboratory of Rail Traffic Control and Safety BJTU Hong Kong

ISBN: (纸本)9781612842547

Kolmogorov-Smirnov (K-S) test-a non-parametric method to measure the goodness of fit, is applied for automatic modulation classification (AMC) in this paper. The basic procedure involves computing the empirical cumulative distribution function (ECDF) of some decision statistic derived from the received signal, and comparing it with the CDFs of the signal under each candidate modulation format. The K-S-based modulation classifier is first developed for AWGN channel, then it is applied to OFDM-SDMA systems to cancel multiuser interference. Regarding the complexity issue of K-S modulation classification, we propose a low-complexity method based on the robustness of the K-S classifier. Extensive simulation results demonstrate that compared with the traditional cumulant-based classifiers, the proposed K-S classifier offers superior classification performance and requires less number of signal samples (thus is fast).

关键词： automatic modulation classification Kolmogorov-Smirnov test OFDM interference cancellation

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Utilizing Side Information in modulation classification for Wireless OFDM Systems with Adaptive modulation

Utilizing Side Information in Modulation Classification for ...

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IEEE 74th Vehicular Technology Conference (VTC)

作者： Haering, L. Chen, Y. Czylwik, A. Univ Duisburg Essen Dept Commun Syst Essen Germany

ISBN: (纸本)9781424483273

This paper presents a framework of maximum-a-posteriori (MAP) algorithms for the automatic modulation classification (AMC) in orthogonal frequency division multiplexing (OFDM) based communication systems with adaptive modulation (AM). The proposed classifiers intensively utilize side information typically available in wireless time-division duplex (TDD) systems that is channel reciprocity, the known frame structure and the knowledge about the total transmission data rate. As the computational complexity of the optimal algorithms is rather high, a metric approximation is used whose accuracy increases with rising signal-to-noise power ratio (SNR). Numerical results show that the system performance degradation in terms of the packet-error ratio (PER) due to erroneously detected modulation schemes is small in typical wireless communication scenarios if the proposed AMC algorithm is applied.

关键词： AM AMC algorithm Adaptive systems Bandwidth Channel estimation MAP algorithms modulation OFDM OFDM modulation PER Receivers SNR TDD systems Wireless communication adaptive modulation adaptive modulation automatic modulation classification channel reciproc

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A waveform digitizer-based automatic modulation classifier for a flexible spectrum management

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MEASUREMENT 2011年第6期44卷 1007-1017页

作者： Bjorsell, Niclas De Vito, Luca Rapuano, Sergio Univ Sannio Dept Engn Benevento Italy Univ Gavle ITB Elect Gavle Sweden

The paper presents the development and validation of an automatic digital modulation classifier based on a waveform digitizer architecture. The proposed automatic digital modulation classifier can be used for signal recognition in the next generation telecommunication systems, characterized by a flexible and dynamic management of the radio spectrum. It has been implemented on a PC architecture, connected with two different types of waveform digitizers. The experimental validation has been carried out by means of actual telecommunication signals, even in presence of narrowband and wideband interference. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： automatic modulation classification Spectrum management

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Cyclostationarity Feature-Based Detection and classification

Cyclostationarity Feature-Based Detection and Classification

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作者： Amy C. Malady Virginia Polytechnic Institute and State University

学位级别：硕士

Cyclostationarity feature-based (C-FB) detection and classification is a large field of research that has promising applications to intelligent receiver design. Cyclostationarity FB classification and detection algorithms have been applied to a breadth of wireless communication signals – analog and digital alike. This thesis reports on an investigation of existing methods of extracting cyclostationarity features and then presents a novel robust solution that reduces SNR requirements, removes the pre-processing task of estimating occupied signal bandwidth, and can achieve classification rates comparable to those achieved by the traditional method while based on only 1/10 of the observation time. Additionally, this thesis documents the development of a novel low order consideration of the cyclostationarity present in Continuous Phase modulation (CPM) signals, which is more practical than using higher order cyclostationarity. Results are presented – through MATLAB simulation – that demonstrate the improvements enjoyed by FB classifiers and detectors when using robust methods of estimating cyclostationarity. Additionally, a MATLAB simulation of a CPM C-FB detector confirms that low order C-FB detection of CPM signals is possible. Finally, suggestions for further research and contribution are made at the conclusion of the thesis.

关键词： automatic modulation classification Detection Cyclostationarity Continuous Phase modulation Robust Estimation

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Cyclostationarity Feature-Based Detection and classification

Cyclostationarity Feature-Based Detection and Classification

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作者： Malady, Amy Colleen Virginia Tech | University

Cyclostationarity feature-based (C-FB) detection and classification is a large field of research that has promising applications to intelligent receiver design. Cyclostationarity FB classification and detection algorithms have been applied to a breadth of wireless communication signals â analog and digital alike. This thesis reports on an investigation of existing methods of extracting cyclostationarity features and then presents a novel robust solution that reduces SNR requirements, removes the pre-processing task of estimating occupied signal bandwidth, and can achieve classification rates comparable to those achieved by the traditional method while based on only 1/10 of the observation time. Additionally, this thesis documents the development of a novel low order consideration of the cyclostationarity present in Continuous Phase modulation (CPM) signals, which is more practical than using higher order cyclostationarity. Results are presented â through MATLAB simulation â that demonstrate the improvements enjoyed by FB classifiers and detectors when using robust methods of estimating cyclostationarity. Additionally, a MATLAB simulation of a CPM C-FB detector confirms that low order C-FB detection of CPM signals is possible. Finally, suggestions for further research and contribution are made at the conclusion of the thesis.

关键词： robust estimation continuous phase modulation cyclostationarity detection automatic modulation classification Thesis

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Cyclostationarity-Based modulation classification of Linear Digital modulations in Flat Fading Channels

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WIRELESS PERSONAL COMMUNICATIONS 2010年第4期54卷 699-717页

作者： Dobre, Octavia A. Abdi, Ali Bar-Ness, Yeheskel Su, Wei Mem Univ Newfoundland Fac Engn & Appl Sci St John NF A1B 3X5 Canada New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA RDECOM Ft Monmouth NJ 07703 USA

modulation classification is an intermediate step between signal detection and demodulation, and plays a key role in various civilian and military applications. In this correspondence, higher-order cyclic cumulants (CCs) are explored to discriminate linear digital modulations in flat fading channels. Single- and multi-antenna CC-based classifiers are investigated. These benefit from the robustness of the CC-based features to unknown phase and timing offset. Furthermore, the latter provides significant performance improvement due to spatial diversity used to combat the fading effect. Classifier performances are investigated under a variety of channel conditions. In addition, analytical closed-form expressions for the cyclic cumulant polyspectra of linearly digitally modulated signals affected by fading, carrier frequency and timing offsets, and additive Gaussian noise are derived, along with a condition for the oversampling factor to avoid aliasing in the cycle and spectral frequency domains.

关键词： Antenna arrays automatic modulation classification Cycle aliasing Higher-order cyclic statistics Probability of correct classification Selection combining

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Fast and Robust modulation classification via Kolmogorov-Smirnov Test

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IEEE TRANSACTIONS ON COMMUNICATIONS 2010年第8期58卷 2324-2332页

作者： Wang, Fanggang Wang, Xiaodong Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100088 Peoples R China Columbia Univ Dept Elect Engn New York NY 10027 USA

A new approach to modulation classification based on the Kolmogorov-Smirnov (K-S) test is proposed. The K-S test is a non-parametric method to measure the goodness of fit. The basic procedure involves computing the empirical cumulative distribution function (ECDF) of some decision statistic derived from the received signal, and comparing it with the CDFs or the ECDFs of the signal under each candidate modulation format. The K-S-based modulation classifiers are developed for various channels, including the AWGN channel, the flat-fading channel, the OFDM channel, and the channel with unknown phase and frequency offsets, as well as the non-Gaussian noise channel, for both QAM and PSK modulations. Extensive simulation results demonstrate that compared with the traditional cumulant-based classifiers, the proposed K-S classifiers offer superior classification performance, require less number of signal samples (thus is fast), and is more robust to various channel impairments.

关键词： automatic modulation classification Kolmogorov-Smirnov test fading OFDM frequency offset non-Gaussian noise

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AMC Improvements from Robust Estimation

AMC Improvements from Robust Estimation

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IEEE Global Telecommunications Conference (GLOBECOM 2010)

作者： Malady, Amy C. Beex, A. A. (Louis) Virginia Tech Dept Elect & Comp Engn Wireless VT DSPRL Blacksburg VA 24061 USA

ISBN: (纸本)9781424456383

The performance of a cyclostationarity feature based automatic modulation classifier (AMC) is improved by the novel usage of a robust estimate of second order first conjugate cyclostationarity. Using a previously proposed statistical test for identifying cyclostationarity, we show that the distribution of the test statistic at a cycle frequency has larger mean and smaller variance - when it is based on a robust estimate of the second order first conjugate cyclic temporal moment function (CTMF) than when a classical estimate of the second order first conjugate CTMF is used. The improvements are a 4 dB reduction in SNR requirements, a lower false alarm rate, and reduced sensitivity to receiver bandwidth - when the test uses the robust estimate.

关键词： automatic modulation classification cyclostationarity robust estimation

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Cognitive Radio and Networking Research at Virginia Tech

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PROCEEDINGS OF THE IEEE 2009年第4期97卷 660-688页

作者： MacKenzie, Allen B. Reed, Jeffrey H. Athanas, Peter Bostian, Charles W. Buehrer, R. Michael DaSilva, Luiz A. Ellingson, Steven W. Hou, Y. Thomas Hsiao, Michael Park, Jung-Min Patterson, Cameron Raman, Sanjay da Silva, Claudio R. C. M. Virginia Polytech Inst & State Univ Wireless Virginia Tech Blacksburg VA 24061 USA

More than a dozen wireless @ Virginia Tech faculty are working to address the broad research agenda of cognitive radio and cognitive networks. our core research team spans the protocol stack from radio and reconfigurable hardware to communications theory to the networking layer. our work includes new analysis methods and the development of new software architectures and applications, in addition to work on the core concepts and architectures underlying cognitive radios and cognitive networks. This paper describes these contributions and points towards critical future work that remains to fulfill the promise of cognitive radio. We briefly describe the history of work on cognitive radios and networks at Virginia Tech and then discuss our contributions to the core cognitive processing underlying these systems, focusing on our cognitive engine. We also describe developments that support the cognitive engine and advances in radio technology that provide the flexibility desired in a cognitive radio node. We consider securing and verifying cognitive systems and examine the challenges of expanding the cognitive paradigm up the protocol stack to optimize end-to-end network performance. Lastly, we consider the analysis of cognitive systems using game theory and the application of cognitive techniques to problems in dynamic spectrum sharing and control of multiple-input multiple-output radios.

关键词： automatic modulation classification cognitive networks cognitive radio dynamic spectrum access game theory genetic algorithms multiple-input multiple-output (MIMO) radio-frequency integrated circuit design software defined radio spectrum sensing

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Robust modulation classification for PSK/QAM/ASK using higher-order cumulants

Robust modulation classification for PSK/QAM/ASK using highe...

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6th International Conference on Information, Communications and Signal Processing

作者： Mirarab, M. R. Sobhani, M. A. Malek Ashtar Univ Technol Dept Elect & Commun Engn Tehran Iran

this paper presents a method based on Higher-order cumulants for classifying modulation type of PSK, ASK and QAM signals. The method is robust to the presence of frequency offset. The high performance and robustness o... 详细信息

ISBN: (纸本)9781424409822

关键词： automatic modulation classification higher-order cumulants

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