Analysis on suitable equalizer and Development of an algorithm for Channel estimation in co ofdm system

Abstract

Coherent Optical Orthogonal Frequency-Division Multiplexing (CO-OFDM) has as of late risen as an alluring modulation format for optical communications, and noteworthy advancement has been made through ypothetical investigation and exploratory analysis. CO-OFDM brings to optical communications an integration of two methods, coherent optical detection and Orthogonal Frequency-Division Multiplexing (OFDM). In this research work, two main challenges of CO-OFDM framework are dissected that are non-linear noise equalization and channel estimation. Fiber nonlinearities speak to the essential constraining components to the measure of data that can be transmitted on a single optic fiber. To even out these nonlinear impacts, numerous non-linear equalizers dependent on ANN and SVM were introduced. In spite of the fact that these equalizers give great outcomes, hey had neglected to be transparent to the user and they make more memorization errors. So, a Non-Linear Equalizer (NLE) in light of Adaptive Neuro-Fuzzy Inference System (ANFIS) is displayed for CO-OFDM frameworks to relieve non-linearities on long-haul optical communications with high bit rate and low bit error rate of the framework. Likewise, this research work is centered on the issue of channel estimation in CO-OFDM framework. The impact of optical channel is an important limiting component in CO-OFDM structures when the speed rate is higher. Thus, it requires using efficient channel estimation methods to pursue the channel changes. newline