ABSTRACT

Fuzzy set theory was first introduced by Zadeh (1965). Fuzzy sets and systems have been around for over 50 years and have been accepted as a system-building methodology that can deliver satisfactory performance despite uncertainty and inaccuracies. Type 1 fuzzy logic system (T1 FLS) is the most well-known and widely used type of FLS. Nevertheless, in recent years, there has been a significant increase in research into more complex forms of fuzzy logic, such as the interval type 2 fuzzy logic system (IT2 FLS) and more recently the generic type 2 fuzzy logic system (T2 FLS). Fuzzy probability refers to the special case of inaccurate probabilities associated with the concept of a random set. The Karnik–Mendel (KM) method is not the most accurate defuzzy method. By definition, type 2 fuzzy set (T2 FS) is a fuzzy set, and the membership level of each element is type 1 fuzzy set (T1 FS) of [0, 1]. Digital cellular radio (DCR) communication systems face co-channel interference (CCI), adjacent-channel interference (ACI), and inter-symbol interference (ISI) in the presence of additive white Gaussian noise (AWGN). FLSs have been widely used to handle CAC-related problems in ATM networks as well as traditional connections. It provides a powerful mathematical framework to deal with real-world inaccuracies, and it also shows smooth motion with the ability to better adapt to dynamic, inaccurate, and congested environments.