On the use of singular spectrum analysis for OFDM channel estimation

Over the last decade or so, the data rate and spectrum efficiency of wireless communication systems has been significantly improved with the advent of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology. In order to operate in the most effective way, OFDM-based communication systems need accurate channel estimation. The channel estimation in OFDM communication systems becomes a challenging problem ever since from its inception. Singular Spectrum Analysis (SSA) has proven to be a flexible method for the analysis of time-series data, because of the decomposition derived from signal itself. Empirical orthogonal functions (EOF´s) are derived from lag matrix of the time series. In this paper, the OFDM channel estimation problem is being addressed using SSA. The performance of method is observed in terms of bit error rate (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.