A Blind Recognition Algorithm for Real Orthogonal STBC MC-CDMA Underdetermined Systems Based on LPCA and SCA

This paper proposes a blind recognition algorithm for real orthogonal space–time block code multi-carrier code division multiple access (OSTBC MC-CDMA) underdetermined systems based on Laplacian potential clustering algorithm (LPCA) and sparse component analysis. In our work, the received signal first has been constructed to satisfy the instantaneous underdetermined model, where the mixing matrix (virtual channel matrix) includes the information of space–time block code. The virtual channel matrix is then can be separated by using the LPCA. We show that, for OSTBC, the correlation matrix of virtual channel matrix is a diagonal matrix, while with non-OSTBC (NOSTBC) signal, such correlation matrix of virtual channel matrix was not. According to this property, two characteristic parameters of correlation matrix of virtual channel matrix are extracted, such as sparsity and energy ratio of non-main and main diagonal elements. In recognition process, the energy ratio will be used in pre-decision step, thus it avoids the influence of noise and making sure that the correlation matrix of virtual channel matrix is a diagonal matrix for OSTBC. The last decision will be done through comparing sparsity parameter with the number of transmitted symbols, where the sparsity parameter of OSTBC will be equal the number of transmitted symbols and the such parameter of NOSTBC will not. Simulation results demonstrate the effectiveness of the proposed algorithm.