Graduate School and Research Center in Digital Sciences

FDD massive MIMO channel spatial covariance conversion using projection methods

Miretti, Lorenzo; Cavalcante, Renato L.G.; Stanczak, Slawomir

ICASSP 2018, IEEE International Conference on Acoustics, Speech and Signal Processing, 15-20 April 2018, Calgary, Alberta, Canada

Knowledge of second-order 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 infinite-dimensional 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 state-of-the art solutions in terms of accuracy and complexity, for typical array geometries and duplex gaps.

Document Doi Arxiv Bibtex

Title:FDD massive MIMO channel spatial covariance conversion using projection methods
Keywords:FDD Massive MIMO, covariance matrix, angular reciprocity, projection methods, subspace estimation
Department:Communication systems
Eurecom ref:5526
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Bibtex: @inproceedings{EURECOM+5526, doi = {}, year = {2018}, title = {{FDD} massive {MIMO} channel spatial covariance conversion using projection methods}, author = {{M}iretti, {L}orenzo and {C}avalcante, {R}enato {L}.{G}. and {S}tanczak, {S}lawomir}, booktitle = {{ICASSP} 2018, {IEEE} {I}nternational {C}onference on {A}coustics, {S}peech and {S}ignal {P}rocessing, 15-20 {A}pril 2018, {C}algary, {A}lberta, {C}anada}, address = {{C}algary, {CANADA}}, month = {04}, url = {} }
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