EMD based OFDM channel estimation

In 4G broadband wireless communications, a multiple input multiple output (MIMO) system with orthogonal frequency division multiplexing (OFDM) is the most promising and efficient system for high data rate communication. OFDM effectively mitigates inter symbol interference (ISI) caused by the delay spread, due to the multipath propagation effects, inherently present in the wireless channel. Channel estimation is an integral part of OFDM systems, although the existing techniques differ in terms of bit error rate (BER), it has been observed that many channel estimation techniques are a subset of linear minimum mean square error (LMMSE) technique. The empirical mode decomposition (EMD) is a new time-frequency analysis technique and has a wide range of applications in signal processing. The EMD uses Hilbert-Huang Transform (HHT) calculation to handle nonlinear and non-stationary data to find the intrinsic mode function (IMF) component to analyze the changes in power spectrum over time. In this paper, the OFDM channel estimation problem is being addressed using EMD. Performance of the method is observed in terms of BER calculations for Rayleigh and Rician fading channels. A lower BER compared to least squares (LS) and LMMSE methods demonstrated the efficacy of the proposed method.