IMPROVING RECEIVED SIGNAL IN WIRELESS COMMUNICATION SYSTEMS USING EQUALIZATION TECHNIQUE WITH NEURO FILTER

Abstract

The aim of this paper is to improve the wireless communication quality by damping or removing the inter-symbol interference (ISI) phenomena in these systems. ISI imposed the main obstacles to achieve increased digital transmission rates with required accuracy. Adaptive equalization technique with least mean square algorithm (LMS) is used to reduce or suppress the unwanted signals in communication channels and combat the resulting ISI effect. Finite impulse response (FIR) filter is used as another technique incorporated with LMS algorithm and zero tap detection technique (Zero tap) to enhance the quality of the communication systems . These techniques were used to suppress echoes that arise from non-line-of-sight (NLOS) components in these wireless communication systems. This paper proposed a new model to aid the work of adaptive equalizer using Modified Elman Neural Network (MENN) as a neuro filter with the presence of ISI and Additive White Gaussian Noise (AWGN) .This neuro filter provides the basic approach to acquire signals as input data to the system from noisy signals .The scheme of proposed system in this paper can perform successful tracking without knowing prior knowledge of the signals. Simulations demonstrate the capability of proposed model to generate considerably smoother receiver in the systems that used only adaptive equalizer.