IEEE Transactions on Signal Processing
Projection approximation subspace tracking
IEEE Transactions on Signal Processing
Adaptive tracking of linear time-variant systems by extended RLSalgorithms
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Fast and Stable Subspace Tracking
IEEE Transactions on Signal Processing
Efficient decision feedback equalization for sparse wireless channels
IEEE Transactions on Wireless Communications
Pilot-based channel estimation for OFDM systems by tracking the delay-subspace
IEEE Transactions on Wireless Communications
A discrete-time model for triply selective MIMO Rayleigh fading channels
IEEE Transactions on Wireless Communications
An adaptive multiuser detector with joint amplitude and delay estimation
IEEE Journal on Selected Areas in Communications
Subspace channel tracking for correlated underwater acoustic communication channels
Proceedings of the Seventh ACM International Conference on Underwater Networks and Systems
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Multipath arrivals in many underwater acoustic channels are often cross-correlated and as a result, the path cross-correlation matrix shows a smaller rank than the number of multipath delay taps. Channel tracking error, measured in terms of the signal prediction error, can be significantly reduced by tracking the signal components in the signal subspace as previously demonstrated for a slowly varying channel in which the signal basis vectors can be assumed to be time-invariant. For a rapidly time-varying channel, one needs to track the time variation of the signal basis vectors. A subspace tracker is used in this paper based on a coarse estimate of the channel impulse response (CIR). The channel amplitudes (components) are tracked using a recursive least squares method. Performance of the proposed algorithms is demonstrated with real sea data and compared with that obtained with conventional approaches. The results demonstrate the importance of tracking the channel basis vectors as well as the channel components.