A low complexity modulation classification algorithm for MIMO systems
Yükleniyor...
Tarih
2013-10
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE-INST Electrical Electronics Engineers Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Automatic modulation classification, Multiple-input multiple-output, Fourth-order cumulant, Blind equalizers, Channel estimation, MIMO, Modulation, Signal to noise ratio, Vectors, LRT, MIMO systems, Asymptotic likelihood function, Blind channel estimation, Channel matrix, Computational complexity, Decision making, Discriminating features, Estimated feature vector, Estimated transmit signal stream, Likelihood ratio test, Low complexity modulation classification, Noise variance, Perfect channel knowledge, Spatial multiplexing systems, MIMO communication, Space division multiplexing
Kaynak
IEEE Communications Letters
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
17
Sayı
10
Künye
Muhlhaus, M. S., Öner, M. M., Dobre, O. A. & Jondral, F. K. (2013). A low complexity modulation classification algorithm for MIMO systems. IEEE Communications Letters, 17(10), 1881-1884. doi:10.1109/LCOMM.2013.091113.130975
