Yazar "Georghiades, Costas N." seçeneğine göre listele

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    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]
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    Joint ML timing and phase estimation in OFDM systems using the EM algorithm
    (IEEE, 2000) Panayırcı, Erdal; Georghiades, Costas N.
    In this paper, a computationally efficient algorithm is presented for joint maximum likelihood (ML) timing and carrier phase estimation of OFDM systems employing M-PSK modulation scheme with additive Gauissian noise, based on the Expectation-Maximization (EM) algorithm. A nondata-aided(NDA) scheme is considered for the joint timing and phase synchronizer which maximizes the low SNR limit of the likelihood function averaged over the M-PSK signal costellation. For this, an Ehl algorithm is derived which estimates the timing offset and the phase rotations of each subcarrier iteratively and which converges to the true ML estimation of the unknown timing and phase. It is shown that the algorithm becomes independent of the signal-to-noise ratio for both low and high SNR cases. The algorithm is applied to the QPSK modulated OFDM systems and it is concluded that for SNR values greater than 10 dB the convergence is achieved in first iteration and for SNR values less than 10 dB, at most in three iterations. It is also concluded that the convergence is independent of the initial starting points.
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    Non-data-aided ML carrier frequency and phase synchronization in OFDM systems
    (Wiley-Blackwell, 2001-04) Panayırcı, Erdal; Georghiades, Costas N.; Huq, Ayesha T.
    In this paper non-data-aided(NDA), maximum likelihood(ML) algorithms are derived for the carrier frequency and phase offset, separately, for OFDM systems employing M-PSK modulation scheme. NDA ML estimation algorithm for frequency offset estimation exploits the redundant information contained in the cyclic prefix preceeding the OFDM symbols, thus reducing the need for pilots. Its mean-squared performance is obtained analytically and compared with simulation results. It is observed that the resulting algorithm generates very accurate estimation even when the offset is high. It is also shown that the frequency estimator may be used in a tracking mode. The ML algorithm derived for the carrier phase estimation is also a non-data-aided(NDA) and maximizes the low SNR limit of the likelihood function averaged over M-PSK signal constellation. It is shown that for sufficiently small SNR the ML phase estimator obtained reduces to the familiar Mth order power synchronizer which belongs to the class of NDA feedforward carrier synchronizers introduced earlier in the literature. Its mean-squared performance is obtained analytically and compared with simulation results. We observe that the resulting algorithm generates very accurate estimation even when the phase offset is high, that the self noise is absent and the performance of the algorithm is basically the same as the Cramer-Rao bound for moderate to high SNR. Finally we note that the error variance derived for the mean-squared performance of this NDA ML synchronizer is an extension of the approximate variance formula appeared in Reference 20,equation(14) for M-PSK.