Polar coordinate quantizers that minimize mean-squared error

Polar coordinate quantizers that minimize mean-squared error Voran, Stephen D. ; Scharf, Louis L. "This work was supported by the Office of Naval Research under contract No. N00014-89-J-1070 and by the NSF Center for Optoelectronic Computing Systems at the University of Colorado, under contract No. 8622236." A quantizer for complex data is defined by a partition of the complex plane and a representation point associated with each cell of the partition. A polar coordinate quantizer independently quantizes the magnitude and phase angle of complex data. We derive design equations for minimum mean-squared error polar coordinate quantizers and report some interesting theoretical results on their performance, including performance limits for "phase-only" representations. The results provide a concrete example of a biased estimator whose mean-squared error is smaller than that of any unbiased estimator. Quantizer design examples show the relative importance of magnitude and phase encoding. Colorado State University. Libraries 1994 text ; image application/pdf ECElls00007.pdf FACFECEN100396ARTI eng c1994 IEEE

Polar coordinate quantizers that minimize mean-squared error

Voran, Stephen D. ; Scharf, Louis L.

"This work was supported by the Office of Naval Research under contract No. N00014-89-J-1070 and by the NSF Center for Optoelectronic Computing Systems at the University of Colorado, under contract No. 8622236."

A quantizer for complex data is defined by a partition of the complex plane and a representation point associated with each cell of the partition. A polar coordinate quantizer independently quantizes the magnitude and phase angle of complex data. We derive design equations for minimum mean-squared error polar coordinate quantizers and report some interesting theoretical results on their performance, including performance limits for "phase-only" representations. The results provide a concrete example of a biased estimator whose mean-squared error is smaller than that of any unbiased estimator. Quantizer design examples show the relative importance of magnitude and phase encoding.

Colorado State University. Libraries

1994

text ; image

application/pdf

ECElls00007.pdf

FACFECEN100396ARTI

eng

c1994 IEEE