Role of Fractional Powers in Maneuvering the Fractional Lower-Order Auto-Covariance of Skewed Alpha-Stable Signals in Gaussian Noise Environment

Abstract

Since, alpha-stable noise signals similarity can only be gauged by Fractional Lower-Order Auto-Covariance (FLOAC), therefore, the role of impulsiveness and skewness parameters, in generation and detection of the skewed alphastable (SkαS) noise signals, has been analyzed several times in the past. However, in this paper, a thorough analysis on the role of fractional powers in changing the FLOAC of SkαS noise signals has been carried out. The two associated fractional powers of FLOAC has been maneuvered in three possible ways to observe the probable trend of SkαS noise signals in the presence and absence of Gaussian noise. According to the observed results, the fractional powers largely and solely affect the FLOAC when they are manipulated collaboratively or even individually where the analyzed results can be handy in enhancing many SkαS noise signal processing techniques, especially, in the detection of SkαS noise carrier signals in Random Communication Systems.