The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Spectral Correlation of Modulated Signals: Part I--Analog Modulation
Abstract
The importance of the concept of cyclostationarity in design and analysis of signal detectors, synchronizers, and extractors in communication systems is briefly discussed, and the central role of spectral correlation, in the characterization of random processes that are cyclostationary in the wide sense, is explained. A spectral correlation function that is a generalization of the power spectral density function is described, and a corresponding generalization of the Wiener-Khinchine relation and several other fundamental spectral correlation relations also are described. Explicit formulas for the spectral correlation function for various types of analog-modulated signals are derived. This includes pulse and carrier amplitude modulation, quadrature amplitude carrier modulation, and phase and frequency carrier modulation. To illustrate the differing spectral correlation characteristics of different modulation types, the magnitudes of the spectral correlation functions are graphed or described in graphical terms as the heights of surfaces above a bifrequency plane.
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Cites
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Gardner, W. A., & Robinson, E. A. (1989) · Journal of Dynamic Systems, Measurement, and Control · doi:10.1115/1.3153112 · Cited by 617
Self-citationSignal interception: a unifying theoretical framework for feature detection
Gardner, W. A. (1988) · IEEE Transactions on Communications · doi:10.1109/26.3769 · Cited by 609
Self-citationCharacterization of cyclostationary random signal processes
Gardner, W., & Franks, L. (1975) · IEEE Transactions on Information Theory · doi:10.1109/tit.1975.1055338 · Cited by 422
Self-citationSpectral Correlation of Modulated Signals: Part II--Digital Modulation
Gardner, W., Brown, W., & Chen, C.-K. (1987) · IEEE Transactions on Communications · doi:10.1109/tcom.1987.1096816 · Cited by 408
Self-citationThe spectral correlation theory of cyclostationary time-series
Gardner, W. A. (1986) · Signal Processing · doi:10.1016/0165-1684(86)90092-7 · Cited by 299
Self-citationJournal of Multivariate Analysis
Krishnaiah, P. R. (2005) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess1313 · Cited by 187
PERIODIC AUTOREGRESSIVE‐MOVING AVERAGE (PARMA) MODELING WITH APPLICATIONS TO WATER RESOURCES1
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Zeng, Y., & Liang, Y.-C. (2009) · IEEE Transactions on Communications · doi:10.1109/tcomm.2009.06.070402 · Cited by 1,258
Deep Learning Models for Wireless Signal Classification With Distributed Low-Cost Spectrum Sensors
Rajendran, S., Meert, W., Giustiniano, D., Lenders, V., & Pollin, S. (2018) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2018.2835460 · Cited by 868
A new approach to signal classification using spectral correlation and neural networks
Fehske, A., Gaeddert, J., & Reed, J. H. (2005) · First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005. · doi:10.1109/dyspan.2005.1542629 · Cited by 447
Spectral Correlation of Modulated Signals: Part II--Digital Modulation
Gardner, W., Brown, W., & Chen, C.-K. (1987) · IEEE Transactions on Communications · doi:10.1109/tcom.1987.1096816 · Cited by 408
Self-citationMaximum-Minimum Eigenvalue Detection for Cognitive Radio
Zeng, Y., & Liang, Y.-C. (2007) · 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications · doi:10.1109/pimrc.2007.4394211 · Cited by 327
Metadata
- Authors
- Gardner, W.
- Venue
- IEEE Transactions on Communications
- Published
- 1987-06
- Volume
- 35
- Issue
- 6
- Pages
- 584-594
- ISSN
- 0096-2244 (ISSN-L)
- OpenAlex
- W2048101164
- Cited by
- 302
- References
- 11
- FWCI
- 5.11
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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