Title :
A Low Complexity Modulation Classification Algorithm for MIMO Systems
Author :
Muhlhaus, M.S. ; Oner, M. ; Dobre, Octavia A. ; Jondral, Friedrich K.
Author_Institution :
Karlsruhe Inst. of Technol., Karlsruhe, Germany
Abstract :
A novel algorithm is proposed for automatic modulation classification in multiple-input multiple-output spatial multiplexing systems, which employs fourth-order cumulants of the estimated transmit signal streams as discriminating features and a likelihood ratio test (LRT) for decision making. The asymptotic likelihood function of the estimated feature vector is analytically derived and used with the LRT. Hence, the algorithm can be considered as asymptotically optimal for the employed feature vector when the channel matrix and noise variance are known. Both the case with perfect channel knowledge and the practically more relevant case with blind channel estimation are considered. The results show that the proposed algorithm provides a good classification performance while exhibiting a significantly lower computational complexity when compared with conventional algorithms.
Keywords :
MIMO communication; channel estimation; computational complexity; decision making; modulation; space division multiplexing; LRT; MIMO systems; asymptotic likelihood function; automatic modulation classification; blind channel estimation; channel matrix; computational complexity; decision making; discriminating features; estimated feature vector; estimated transmit signal streams; fourth-order cumulants; likelihood ratio test; low complexity modulation classification; multiple-input multiple-output systems; noise variance; perfect channel knowledge; spatial multiplexing systems; Blind equalizers; Channel estimation; MIMO; Modulation; Signal to noise ratio; Vectors; Automatic modulation classification; fourth-order cumulant; multiple-input multiple-output;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2013.091113.130975