Subspace-based Blind Channel Estimation for MIMO-OFDM Systems with Repetition Index

A subspace-based blind channel estimation algorithm for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this paper. The proposed algorithm for MIMO-OFDM systems generalizes the conventional repetition index approach, which is only suitable for single-input single-output (SISO)-OFDM systems. Additionally, the necessary conditions of the proposed algorithm to be full row rank are discussed. Simulation results show that the probability of full row rank of the proposed signal matrix is close to one for different constellation schemes. The proposed generalized approach also outperforms the conventional approach with virtual carriers (VCs) in terms of normalized mean-squared error (NMSE) under static channel environments even if the number of OFDM symbols is small.