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Yazar "Dobre, Octavia Adina" seçeneğine göre listele

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    Automatic modulation classification for mimo systems using fourth-order cumulants
    (IEEE, 2012) Mühlhaus, Michael S.; Öner, Mustafa Mengüç; Dobre, Octavia Adina; Jkel, Holger U.; Jondral, Friedrich K.
    Automatic classification of the modulation type of an unknown communication signal is a challenging task, with applications in both commercial and military contexts, such as spectrum surveillance, cognitive radio, and electronic warfare systems. Most of the automatic modulation classification (AMC) algorithms found in the literature assume that the signal of interest has been transmitted using a single antenna. In this paper, a novel AMC algorithm for multiple input multiple output (MIMO) signals is proposed, which employs fourth-order cumulants as features for classification. First, perfect channel state information (CSI) is assumed. Subsequently, a case of more practical relevance is considered, where the channel matrix is unknown and has to be estimated blindly by employing independent component analysis (ICA). The performance of the proposed classification algorithm is investigated through simulations and compared with an average likelihood ratio test (ALRT) which can be considered as optimum in the Bayesian sense, but has a very high computational complexity.
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    Cyclostationarity-based robust algorithms for QAM signal identification
    (IEEE-INST Electrical Electronics Engineers Inc, 2012-01) Dobre, Octavia Adina; Öner, Mustafa Mengüç; Rajan, Sreeraman; Inkol, Robert
    This letter proposes two novel algorithms for the identification of quadrature amplitude modulation (QAM) signals. The cyclostationarity-based features used by these algorithms are robust with respect to timing, phase, and frequency offsets, and phase noise. Based on theoretical analysis and simulations, the identification performance of the proposed algorithms compares favorably with that of alternative approaches.
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    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.
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    A novel algorithm for MIMO signal classification using higher-order cumulants
    (IEEE, 2013) Muehlhaus, Michael S.; Öner, Mustafa Mengüç; Dobre, Octavia Adina; Jaekel, Holger U.; Jondral, Friedrich K.
    Automatic modulation classification (AMC) of unknown communications signals is employed in both commercial and military applications, such as cognitive radio, spectrum surveillance, and electronic warfare. Most of the AMC methods proposed in the literature are developed for systems with a single transmit antenna. In this paper, an AMC algorithm for multiple-input multiple-output (MIMO) signals is proposed, which is based on higher-order cumulants. The use of cumulants with different orders, as well as their combinations as feature vectors are investigated. The ideal case of a priori knowledge of the channel state information (CSI) is considered, along with a setting of practical relevance, where the channel matrix is blindly estimated through independent component analysis. The performance of the proposed algorithm with different features is evaluated through simulations and compared with that of the average likelihood ratio test (ALRT).
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    On the second-order cyclic statistics of signals in the presence of receiver impairments
    (IEEE-INST Electrical Electronics Engineers Inc, 2011-12) Öner, Mustafa Mengüç; Dobre, Octavia Adina
    Cyclostationary characteristics of communication signals can be exploited for performing various signal processing tasks. Receiver impairments that affect the cyclic statistics of signals may lead to a degradation in the performance of cyclostationarity-based signal processing algorithms. Inphase/quadrature (I/Q) imbalance, oscillator phase noise, and random sampling jitter can be counted amongst the typical receiver impairments encountered in wireless communication systems. In this work, we investigate the effects of these nonidealities on the second-order cyclic statistics of baseband communication signals. General results are derived for arbitrary complex-valued (and possibly improper) signals, and examples are provided for cases of practical interest.
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    Signal identification for multiple-antenna wireless systems: achievements and challenges
    (IEEE, 2016-01-18) Eldemerdash, Yahia A.; Dobre, Octavia Adina; Öner, Mustafa Mengüç
    Signal identification is an umbrella term for signal processing techniques designed for the identification of the transmission parameters of unknown or partially known communication signals. Initially a key technology for military applications such as signal interception, radio surveillance and electronic warfare, signal identification techniques recently found applications in commercial wireless communications as an enabling technology for cognitive receivers. With the advance and rapid adoption of multiple-input multiple-output (MIMO) communication systems in the last decade, extension of signal identification methods to include this transmission paradigm has become a priority and focus of intensive research efforts. The aim of this work is to provide a comprehensive state-of-the-art survey on algorithms proposed for the new and challenging signal identification problems specific to MIMO systems, including space-time block code (STBC) identification, MIMO modulation identification, and detection of the number of transmit antennas. Finally, concluding remarks on MIMO signal identification are provided along with an outline of the open problems and future research directions.
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    Special issue on cognitive radio: The road for its second decade
    (Elsevier Science BV, 2013-12) Baddour, Kareem E.; Bar-Ness, Yeheskel; Dobre, Octavia Adina; Öner, Mustafa Mengüç; Serpedin, Erchin; Spagnolini, Umberto
    [No abstract available]

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