Relationship Between Two Distortion Measures for Memoryless Nonlinear Systems

Memoryless nonlinear transforms of random signals with Gaussian statistics are encountered in a variety of signal processing applications. A well-known criterion for the description of distortion errors is the Mean Squared Error (MSE) between the input and output signals of the nonlinearity. A diffe...

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Bibliographic Details
Published inIEEE signal processing letters Vol. 17; no. 11; pp. 917 - 920
Main Author Zillmann, Peter
Format Journal Article
LanguageEnglish
Published New York IEEE 01.11.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Criteria
Distortion
Distortion measurement
Dynamic range
Dynamical systems
Errors
Gaussian
Gaussian signal
memoryless nonlinearity
Noise
Nonlinear distortion
Nonlinearity
Optimization
Quantization
Signal processing
Statistics
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Summary:Memoryless nonlinear transforms of random signals with Gaussian statistics are encountered in a variety of signal processing applications. A well-known criterion for the description of distortion errors is the Mean Squared Error (MSE) between the input and output signals of the nonlinearity. A different criterion which has been found to be useful especially in the field of multicarrier communications is the Signal-to-Distortion Noise Ratio (SDNR), which is based on the BUSSGANG decomposition of the output of the nonlinearity. It is shown that the SDNR optimum coincides with the minimum MSE solution, which simplifies the optimization of memoryless nonlinear functions with respect to SDNR. The results are applied to quantization and dynamic range reduction of Gaussian signals.
Bibliography:ObjectType-Article-2
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2010.2072498