Abstract
Noise estimation has been used majorly in imaging processing and voice speech recognition applications. Therefore, researchers have found optimal solutions to non-stationary noise estimation. Particularly, there is a proposed method that estimates spectral noise in a noisy speech signal which is based on two observations; speech pauses and approximation of power spectral densities of the noisy signal to the true noise during speech pauses. Though from recent studies, the observations obtained cannot be inferred for other types of signals especially RF signals and have not been tested on signals in the frequency domain, this paper bridges that gap of research and presents the results, analysis, and conclusion on the findings concerning the noise estimation with RF signals using an extension of the proposed method in the frequency domain. It presents a detailed methodology of implementation of the minimum statistics method for noise estimation in python 3 code which was tested with RF signals and thus met the requirement of dynamic thresholding with spectrum occupancy measurement.
Highlights
Noise variation occurs not just in frequency but in time (Series, 2017) and a preferred solution is one that is able to consider the frequency- and time- dependent noise levels in occupancy measurement
This paper presents a nuanced version of the method of minimum statistics in noise estimation of RF signals for spectrum occupancy measurement implemented in Python 3.6
The noise estimation algorithm was combined with multiplicatively modified minimum mean square error log spectral amplitude (MM-MMSELSA) estimator (Ephraim & Malah, 1985; Malah, et al, 1999) and the 2400bps MELP speech coder (McCree, et al, 1996)
Summary
Noise variation occurs not just in frequency but in time (Series, 2017) and a preferred solution is one that is able to consider the frequency- and time- dependent noise levels in occupancy measurement. This is because a strong emission in one channel may produce an increase in the noise level in neighbouring channels due to the phase noise of the transmitter. Some methods have been proposed by the International Telecommunication Union (ITU) to achieve dynamic thresholding in the spectrum occupancy measurement One of such methods uses the frequencies of an unused channel such that the threshold is calculated from the levels measured throughout one scan.
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