ADDITIVE INTERFERENCE CANCELLATION IN CDMA SYSTEM USING ADAPTIVE NEURO-FUZZY NETWORK

Abstract

The appearance of 3G communication standards represented by W CDMA (Europe) and CDMA2000 (Korea) has overcome difficulties of previous systems about subscriber capacity, security, data rate, ... Interference cancellation for these systems have been researched carefully. CDMA systems are affected by many kinds of noise such as: fading, interference, MAI.... Although additive noise has no more effcient to quality of CDMA services because these systems use modern spread-spectrum technique. But in many environment has small E/No ratio, this effect is significant and can not be ignored. This paper introcudes a noise cancellation technique for DS-CDMA system. This technique gives a network structure combined from fuzzy logic and neural network to reduce effect of additive noise in received signal. This structure is very flexible, it means that we can modify this structure depend on transmitted environment conditions. This combination improves the both advantages: trainned ability of neuro-network and fast-response of fuzzy logic.