Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Fundamentals of WiMAX: Understanding Broadband Wireless Networking (Prentice Hall Communications Engineering and Emerging Technologies Series)
Wireless Channel Tracking Based on Optimum Predictive LMS
Wireless Personal Communications: An International Journal
IEEE Transactions on Wireless Communications
Joint data QR-detection and Kalman estimation for OFDM time-varying Rayleigh channel complex gains
IEEE Transactions on Communications
Prediction in LMS-type adaptive algorithms for smoothly timevarying environments
IEEE Transactions on Signal Processing
An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
IEEE Transactions on Signal Processing - Part II
Multi-input multi-output fading channel tracking and equalizationusing Kalman estimation
IEEE Transactions on Signal Processing
Autoregressive modeling for fading channel simulation
IEEE Transactions on Wireless Communications
IEEE Transactions on Consumer Electronics
IEEE Transactions on Signal Processing
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This paper deals with multipath channel estimation for Orthogonal Frequency-Division Multiplexing systems under slow to moderate fading conditions. Most of the conventional methods exploit only the frequency-domain correlation by estimating the channel at pilot frequencies, and then interpolating the channel frequency response. More advanced algorithms exploit in addition the time-domain correlation, by employing Kalman filters based on the approximation of the time-varying channel. Adopting a parametric approach and assuming a primary acquisition of the path delays, channel estimators have to track the complex amplitudes of the paths. In this perspective, we propose a less complex algorithm than the Kalman methods, inspired by second-order Phase-Locked Loops. An error signal is created from the pilot-aided Least-Squares estimates of the complex amplitudes, and is integrated by the loop to carry out the final estimates. We derive closed-form expressions of the mean squared error of the algorithm and of the optimal loop coefficients versus the channel state, assuming a Rayleigh channel with Jakes' Doppler spectrum. The efficiency of our reduced complexity algorithm is demonstrated, with an asymptotic mean squared error lower than the first-order auto-regressive Kalman filters reported in the literature, and almost the same as a second-order Kalman-based algorithm.