Roger A. Dalke

Abstract: Digital signal processing algorithms are commonly used to obtain radio spectrum estimates based on measurements. Such algorithms allow the user to apply a variety of time–domain windows and the discrete Fourier transform to RF signals and noise. The purpose of this report is to provide a description of how signal processing options such as window type, duration, and sampling rate affect power spectrum estimates. Power spectrum estimates for periodic RF signals and random processes (stationary and cyclostationary) are analyzed. The results presented can be used to select signal processing parameters and window types that minimize errors and uncertainties.

Keywords: radio spectrum; power spectrum; radio noise; discrete Fourier transform; equivalent noise bandwidth; spectrum measurement

For technical information concerning this report, contact:

Michael G. Cotton
Institute for Telecommunication Sciences
7205527970
mcotton@ntia.gov

To request a reprint of this report, contact:

Lilli Segre, Publications Officer
Institute for Telecommunication Sciences
(303) 497-3572
LSegre@ntia.gov

Disclaimer: Certain commercial equipment, components, and software may be identified in this report to specify adequately the technical aspects of the reported results. In no case does such identification imply recommendation or endorsement by the National Telecommunications and Information Administration, nor does it imply that the equipment or software identified is necessarily the best available for the particular application or uses.

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