Blind channel identification technique in OFDM-based SIMO systems

A subspace-based method is proposed for estimating the channel responses of single-input-multiple-output (SIMO) Orthogonal Frequency Division Multiplexing (OFDM) system. Our technique relies on minimum noise subspace (MNS) decomposition to obtain noise subspace in a parallel structure from a set of pairs (combinations) of system outputs that form a properly connected sequence (PCS). The developed MNS-OFDM estimator is more efficient in computation than subspace (SS)-OFDM estimator, although the former is less robust to noise than the later. To maximize the MNS-OFDM estimator performance, a symmetric version of MNS (SMNS) is implemented. We present simulation results demonstrating the channel identification performance of the corresponding OFDM-based SIMO systems employ cyclic prefixing approach.