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Yayın Eurasip journal on wireless commuication and networking: Editorial(Springer International Publishing, 2005-04-15) Panayırcı, Erdal; Georghiades, Costas N.; Wang, Xinheng; Çırpan, Hakan Ali[No abstract available]Yayın A low-complexity KL expansion-based channel estimator for OFDM systems(Springer International Publishing, 2005-04-05) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, ErdalThis paper first proposes a computationally efficient, pilot-aided linear minimum mean square error (MMSE) batch channel estimation algorithm for OFDM systems in unknown wireless fading channels. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and finds MMSE estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed MMSE estimator. Moreover, optimal rank reduction is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We then consider the stochastic Cramér-Rao bound and derive the closed-form expression for the random KL coefficients and consequently exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE. We also analyze the effect of a modelling mismatch on the estimator performance. To further reduce the complexity, we extend the batch linear MMSE to the sequential linear MMSE estimator. With the fast convergence property and the simple structure, the sequential linear MMSE estimator provides an attractive alternative to the implementation of channel estimator.Yayın Joint modulation classification and antenna number detection for MIMO systems(IEEE, 2016-01-07) Turan, Merve; Öner, Mustafa Mengüç; Çırpan, Hakan AliNoncooperative classification of the modulation type of communication signals finds application in both civilian and military contexts. Existing modulation classification methods for multiple-input multiple-output (MIMO) communication systems commonly require a priori information on the number of transmit antennas employed by the multiantenna transmitter, which, in most of the noncooperative scenarios involving modulation classification, is unknown and needs to be blindly extracted from the received signal. Since the problems of MIMO modulation classification and detection of the number of transmit antennas are highly coupled, we propose a decision theoretic approach for spatial multiplexing MIMO systems that considers these two tasks as a joint multiple hypothesis testing problem. The proposed method exhibits a high performance even in moderate to low SNR regimes while requiring no a priori knowledge of the channel state information and the noise variance.Yayın Cyclostationarity based blind block timing estimation for alamouti coded MIMO signals(IEEE, 2017-06) Gül, Serhat; Öner, Mustafa Mengüç; Çırpan, Hakan AliBlind parameter estimation algorithms provide a powerful tool for application scenarios where the use of training or pilot sequences is not desirable, e.g., in order to improve the bandwidth efficiency of the transmission, or in noncooperative scenarios where such sequences are not available to the receiver. This letter proposes a blind block timing estimation algorithm for Alamouti space-time block coded signals exploiting the second order joint cyclostationary characteristics of the received signal vector, which is induced by the space time block coding operation performed by the transmitter. The proposed algorithm outperforms the existing algorithms by a wide margin.
