Abstract
The method for blind recognition of real orthogonal STBC of underdetermined systems based on sparse component analysis is proposed. This algorithm first built the model of received signals and the virtual channel matrix, as the virtual channel matrix includes information of space time code and can be used for blind recognition, and then the virtual channel matrix is separated by using the DEM algorithm. Finally two characteristic parameters of correlation matrix of virtual channel matrix are extracted according to the characteristics of real orthogonal STBC for blind recognition such as sparsity and energy ratio of non-main and main diagonal elements energy. The simulation results and theoretical analysis indicates that the proposed algorithm can detect signals efficiently and also work well on the lower SNR input.
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Acknowledgment
This work is supported by the National Natural Science Foundation of China (No. 61371164, 61275099, 61102131), the Project of Key Laboratory of Signal and Information Processing of Chongqing (No.CSTC2009CA2003), the Chongqing Distinguished Youth Foundation (No. CSTC2011jjjq40002), the Natural Science Foundation of Chongqing (No. CSTC2012JJA40008), the Research Project of Chongqing Educational Commission (KJ120525, KJ130524) and Graduate Research and Innovation Projects of Chongqing (No. CYS14140).
The authors are grateful to the Chongqing University of Posts and Telecommunication, Chongqing Key Laboratory of Signal and Information Processing (CQKLS&IP) for providing the facility in carrying out this research.
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Raton Mondol, S.I.M.M., Chung, B.Q., Qi, Z.T. (2015). Real Orthogonal STBC MC-CDMA Blind Recognition Based on DEM-Sparse Component Analysis. In: He, X., et al. Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques. IScIDE 2015. Lecture Notes in Computer Science(), vol 9243. Springer, Cham. https://doi.org/10.1007/978-3-319-23862-3_23
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DOI: https://doi.org/10.1007/978-3-319-23862-3_23
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