Abstract
A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit–receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit–receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit–receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods.
Highlights
Multiple-input multiple-output (MIMO) technology has become an active research topic during the last decade due to its capability for achieving the high transmission rates required by an increasing number of data-demanding applications
A performant “ideal” multiple-input multiple-output (MIMO) communication system would require an exact knowledge of the MIMO channel or channel state information (CSI)
Simulations are carried out for a 24 × 24 MIMO system but similar conclusions can be obtained with other MIMO system configurations
Summary
Multiple-input multiple-output (MIMO) technology has become an active research topic during the last decade due to its capability for achieving the high transmission rates required by an increasing number of data-demanding applications. Considering the long distance between the transmit and receive antenna arrays in outdoor scenarios, the above mentioned delay spreading can be assumed to be relatively small It follows that the multipath clusters can be basically described by their mean delays where it seems neither meaningful nor possible to estimate the time delay of each ray constituting the clusters. The minimum description length (MDL) criterion [21,22] is used to track the signal subspace in order to estimate its effective dimension that is changing due to the wireless environment Taking into consideration this phenomenon, the proposed method provides an improved channel mean path delays estimation performance in comparison to the conventional subspace based methods which do not take the scattering in the environment into account
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