Subspace-based blind channel estimation by the signal permutation

There were some problems in the MIMO-OFDM channel estimation with the traditional subspace algorithms, that is slow convergence, this paper proposed an improve subspace channel estimation with the permutations and combinations of the transceiver signal. To get the no correlation between the receiver signal, this paper make some selective choice, after the class Toeplitz extensions of the channel matrix, this paper do the corresponding permutations and combinations for the sending and receiving signal instead of the cumulation of large transmission data blocks, in this way, the algorithms can get the fast increase of the matrix rank which results in a fast convergence of the algorithm. Theoretical analysis and simulation results show the better convergence of the proposed method compared with the traditional subspace algorithms with a slightly increased complexity.