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Yayın A low complexity modulation classification algorithm for MIMO systems(IEEE-INST Electrical Electronics Engineers Inc, 2013-10) Mühlhaus, Michael S.; Öner, Mustafa Mengüç; Dobre, Octavia Adina; Jondral, Friedrich K.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.Yayın Air interface identification for Software Radio systems(Elsevier GMBH, 2007) Öner, Mustafa Mengüç; Jondral, Friedrich K.Reconfigurable Software Radio (SR) equipment is considered as the next evolutionary step in the mobile communications. One of the most crucial properties of a SR terminal is that it is capable of using a wide range of air interface standards, providing a seamless interoperability between different standards and an enhanced roaming capability, paving way to a more flexible and efficient use of spectral resources. This multimode operation has to be supported by a number of key functionalities, one of which is the air interface identification. A SR terminal, when switched on, has to be able to locate and identify the air interfaces available in the frequency environment, and while connected to a network, it has to monitor the presence of alternative air interfaces to perform interstandard handover if necessary. In our work, we propose exploiting the distinct cyclostationary properties of signals from different air interfaces as features for air interface identification.
