Adaptive Channel Modeling for MIMO Wireless Communications
نویسندگان
چکیده
The application of state-space-based subspace system identification methods to training-based estimation for timevarying MIMO frequency-selective channels is explored with the motivation of possible parsimonious parametrization and direct model complexity control. The comparison between the statespace-based channel estimation algorithm and the FIR-based RLS algorithm shows the former is a more robust modeling approach than the later.
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