SPARSE DFT BASED CHANNEL ESTIMATION IN OFDM SYSTEMS

Abstract

Channel estimation is an essential part of Orthogonal Frequency Division Multiplexing (OFDM)communication systems. In this paper, two Discrete Fourier Transform (DFT) improvement algorithms are proposedand compared, where the first one exploits channel sparsity concept while the other considers significant channelcoefficients only. In the proposed algorithms; Enhanced and Sparse DFT (E- DFT and S- DFT), different numberof significant channel components is selected either by a threshold determining procedure such as in E- DFT, orthrough determining channel sparsity level such as in S- DFT. In the presence of Doppler frequency shifts, theInter Symbol Interference (ISI) effect on channel coefficients is successfully reduced using the proposed estimationalgorithms. Vehicular A- ITU channel model is considered with a relatively high vehicle speed up to 68 Km/h inorder to test the suitability of the proposed algorithms for mobile systems. E-DFT and S-DFT improves conventionalas well as previous suggested works on performance improvement of DFT technique (I- DFT). For 64 subcarriers,S- DFT outperforms E- DFT and I- DFT by about 3dB at a BER of 0.01 with mobility reaches 45 Km/h, and byabout 0.4dB and 2.5 dB at a BER of 0.02 with mobility reaches 68 Km/h.