Power Control in CDMA/WCDMA Systems using Neural Network –based Noise-Suppression TechniquePower Control in CDMA/WCDMA Systems using Neural Network –based Noise-Suppression Technique

Abstract

In wireless communication systems, multiple-access techniques introduce multiple access interference and which is one of the major factors that limit the system capacity. For CDMA/WCDMA systems, power is the main resource that is shared by multiple access schemes and thus the performance relies greatly on fast and accurate adaptive power control for both mobile and base stations. The objective of this work is to investigate a neural network-based noise-cancellation system that will further assist the power control techniques. The proposed neural network is trained using Backpropagation learning algorithm to find optimum weight matrix and then optimized weighted value is used to reduce the error level. This reduced error level increases the efficiency of the SIR-based power control system.