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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. FDD Massive MIMO Channel Spatial Covariance Conversion Using Projection Methods
 Institute of Electrical and Electronics Engineers IEEE; IEEE Signal Processing Society: IEEE International Conference on Acoustics, Speech, and Signal Processing 2018. Proceedings : April 1520, 2018, Calgary Telus Convention Center, Calgary, Alberty, Canada Piscataway, NJ: IEEE, 2018 ISBN: 9781538646588 ISBN: 9781538646571 ISBN: 9781538646595 S.36093613 
 International Conference on Acoustics, Speech, and Signal Processing (ICASSP) <2018, Calgary> 

 Englisch 
 Konferenzbeitrag 
 Fraunhofer HHI () 
Abstract
Knowledge of secondorder statistics of channels (e.g. in the form of covariance matrices) is crucial for the acquisition of downlink channel state information (CSI) in massive MIMO systems operating in the frequency division duplexing (FDD) mode. Current MIMO systems usually obtain downlink covariance information via feedback of the estimated covariance matrix from the user equipment (UE), but in the massive MIMO regime this approach is infeasible because of the unacceptably high training overhead. This paper considers instead the problem of estimating the downlink channel covariance from uplink measurements. We propose two variants of an algorithm based on projection methods in an infinitedimensional Hilbert space that exploit channel reciprocity properties in the angular domain. The proposed schemes are evaluated via Monte Carlo simulations, and they are shown to outperform current stateofthe art solutions in terms of accuracy and complexity, for typical array geometries and duplex gaps.