Journal article
A Framework for Statistical Characterization of Indoor Data Traffic for Efficient Dynamic Spectrum Access in the band 2.4 GHz ISM

Publication Details
Ehsan, M.; Dahlhaus, D.
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SDIWC International Journal of Digital Information and Wireless Communications
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The Key for Efficient Dynamic Spectrum Access (DSA) is to model the spectral resources Accurately. A large number of measurement campaigns havebeen Performed to estimate the spectrum usage in outdoor and indoor scenarios. This spectrum usage estimation helps policymakers to optimize the Spectrum Management Methodologies. The spectrum usage studies thus assist Researchers to constitute a way for efficient DSA using prior knowledge of the distribution of the Observed Data traffic in Cognitive Radio (CR) systems. In this paper we extend our previous work Which statistically modeled the Observed Data traffic in the Industrial, Scientific and Medical (ISM) band at 2.4 -GHz in Two Neighboring frequency subband and time slots, respectively, to three Neighboring frequency subbands and timeslots, respectively. As before, the frequency and time correlation functions of the Observed Data traffic are modeled by exponentially decaying to function. The multivariate Gaussian Mixture (MGM) is validated as a good candidate to model the distribution of Measured Data and joint so to estimate the correlation between the Measured Data in Neighboring frequency sub-band and as well as in time domain samples.

Last updated on 2019-25-07 at 10:04