Elements of information theory
Elements of information theory
Microwave Mobile Communications
Microwave Mobile Communications
Optimal insertion of pilot symbols for transmissions over time-varying flat fading channels
IEEE Transactions on Signal Processing
Pilot symbol assisted modulation in frequency selective fadingwireless channels
IEEE Transactions on Signal Processing
Multi-input multi-output fading channel tracking and equalizationusing Kalman estimation
IEEE Transactions on Signal Processing
A factor graph approach to iterative channel estimation and LDPC decoding over fading channels
IEEE Transactions on Wireless Communications
Autoregressive modeling for fading channel simulation
IEEE Transactions on Wireless Communications
IEEE Journal on Selected Areas in Communications
Joint iterative channel estimation and decoding in flat correlated Rayleigh fading
IEEE Journal on Selected Areas in Communications
Blind per-state detection of DPSK over correlated fading channels
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
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We consider a terrestrial wireless channel, whose statistical model under flat-fading conditions is due to Clarke. A lot of papers in the literature deal with receivers for this scenario, aiming at estimating and tracking the time-varying channel, possibly with the aid of known (pilot) symbols. A common approach to derive receivers of reasonable complexity is to resort to a Kalman filter which is based on an approximation of the actual fading process as autoregressive moving-average (ARMA) of a given order. The aim of this paper is to show that the approximation of the actual fading process, usually exploited in the literature, is far from effective. Thus, we present a novel technique, based on an off-line minimization of the mean square error of the channel estimate, which ensures a considerable gain in terms of bit-error rate for Kalman-based receivers without increasing the receiver complexity. Moreover, we also propose a novel approximation, to be employed in Kalman smoothers proposed for iterative detection schemes, which allows further performance improvements without a significant increase of the computational complexity.