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İndeks: Conference Proceedings Citation Index – Science (CPCI-S) × Konu: Channel estimator ×

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Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Yayın
    Maximum a posteriori multipath fading channel estimation for OFDM systems
    (Assoc Elettrotecnica Ed Elettronica Italiana, 2002-10) Panayırcı, Erdal; Çırpan, Hakan Ali
    In this paper, a non-data-aided maximum a posteriori (MAP) channel estimation technique for OFDM systems employing M-PSK modulation scheme is proposed. The technique requires a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve orthogonal expansion and estimates the complex channel parameters of each subcarriers iteratively in frequency domain using the Expectation-Maximization (EM) algorithm. Pilot symbols are employed to choose reliable initial values of the unknown channel parameters. An analytical expression is derived for the exact Cramer-Rao lower bound of the proposed MAP channel estimator. Moreover, robustness of estimator to changes in channel correlation and signal-to-noise ratio is also analyzed. The performance is presented in terms of the mean-square error and the uncoded symbol error rate for a system employing QPSK signaling. Computer simulations demonstrate that the performance of OFDM systems using coherent demodulation based on our channel estimation can be significantly improved.
  • Küçük Resim
    Yayın
    Pilot-aided bayesian MMSE channel estimation for OFDM systems: Algorithm and performance analysis
    (IEEE, 2004) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, Erdal
    This paper proposes a computationally efficient, pilot-aided minimum mean square error (MMSE) channel estimation algorithm for OFDM systems. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and estimates uncorrelated series expansion coefficients. Moreover, optimal rank reduction is achieved in the proposed approach 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 first consider the stochastic Cramer-Rao bound and derive the closed-form expression for the random KL coefficients. We then exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE.