Enhancing Lte Rss for a Robust Path Loss Analysis with Noise Removal
Seyi E. Olukanni, Joseph Isabona, Ituabhor Odesanya · International Journal of Image Graphics and Signal Processing · 2023
Wavelet transform has become a popular tool for signal denoising due to its ability to analyze signals effectively in both time and frequency domains.This is important because the information that is not visible in the time domain can be seen in the frequency domain.However, there are many wavelet families and thresholding techniques (such as haar, Daubechies, symlets, coiflets, meyer Gaussian, morlet, etc) thatare available for the analysis of signals, and choosing the best out of them all is usually time-consuming, thus making it a difficult task for researchers.In this article, we proposed and applied a stepwise expository-based approach to identify the wavelet family and thresholding technique using real-time signal power data acquired from Long-Term Evolution (LTE).We found out from the results that Rigrsure thresholding with the Daubenchies family outperforms others when engaged in practical signal processing.The stepwise expository-based approach will be a relevant guide to effective signal processing over cellular networks, globally.For validation, different datasets were used for the analysis and Rigrsure outperforms the other thresholding techniques.