Performance evaluation of ANN based channel interpolation for OFDM system

Abstract

In this study, the effect of three different techniques that used for interpolation on OFDM system with pilot based comb type channel estimation is investigated and results are given in terms of BER (Bit Error Rate). The estimation of channel at pilot subcarriers is done by LS (Least Square), and interpolation of channel at data subcarriers are obtained by low pass (LP) interpolation algorithm, ANFIS (Adaptive Network Based Fuzzy Inference Systems) and GRNN (Generalized Regression Neural Networks) artificial neural network (ANN) structures. The results show that there is a relationship between the number of used pilot bits and interpolation technique's performance. If the aim is to get high bandwidth efficiency over a given bandwidth LP algorithm should be used for interpolation, to get the lowest BER ANFIS or GRNN can be used. © 2012 IEEE.