18-01-2013, 09:38 AM
Channel Equalization Using Neural Network
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Problem Statement
Design and simulation of artificial neural
network based channel equalizer and its
performance comparison.
Motivation
Digital communication systems are designed to transmit high speed data over communication channels.
During this process the transmitted data is distorted, due to the effects of linear and nonlinear distortions.
In mobile radio channels, frequent changes and multipath causes time dispersion of the digital information known as inter-symbol-interference.
Main objective is to transmit symbols with minimun error.
Area Of Work [1]
CHANNEL EQUALIZATION
Channel distortion calls for channel equalization techniques at the receiver side which reconstructs the transmitted symbols correctly.
Preset equalizer and adaptive equalizer.
Adaptive channel equalizers play an important role in digital communication systems.
Its transfer function is inverse to the transfer function of
the associated channel.
Methodology Used [2]
ARTIFICIAL NEURAL NETWORK
Non linear information (signal) processing devices, which are built from interconnected elementary processing devices called neurons. It has a natural propensity for storing experimental knowledge and making it available for use.
Artificial neural networks (ANNs) can perform complex
mapping between its input and output space and are capable of forming complex decision regions with
nonlinear decision boundaries.