Impulsive Noise Estimator With Minimization Methods (INEMM) on Software

Abstract

This letter introduces the design of an estimator for parameters of Middleton Class A noise using its canonical formula and classical numerical methods. The main focus is to acquire parameters to characterize communication channels in intelligent systems or those based on cognitive paradigms. A comprehensive analysis of the first-order characteristics of the Middleton Class A noise model is conducted to establish the foundational understanding necessary for developing the presented estimator model, named impulsive noise estimator with minimization methods (INEMM). Subsequently, the method is introduced, substantiated, and compared to various established estimators concerning precision and complexity. Results show a distinct advantage in terms of overall performance.