Experimental Investigation of Frequency Domain Channel Extrapolation in Massive MIMO Systems for Zero-Feedback FDD

Estimating downlink (DL) channel state information (CSI) in frequency division duplex (FDD) massive multi-input multi-output (MIMO) systems generally requires pilots and feedback overheads. Accordingly, this paper investigates the feasibility of zero-feedback FDD MIMO based on extrapolation. We use high-resolution parameter estimation (HRPE), specifically space-alternating generalized expectation-maximization (SAGE) algorithm, to extrapolate DL CSI extracted parameters multipath components uplink channel. apply HRPE two different models: vector spatial signature (VSS) model direction arrival (DOA) model. verify these methods through real-world data acquired from measurement campaigns with types sounders: a) a switched array-based, real-time, time-domain, outdoors setup at 3.5 GHz, b) virtual high-accuracy, frequency-domain, indoors 2.4 5-7 GHz. The performance metrics extrapolated channels that we evaluate include mean squared error, beamforming efficiency, spectral efficiency multiuser scenarios. results show HRPE-based extrapolation performs best under simple VSS model, which does not require array calibration, if BS is an open outdoor environment having line-of-sight (LOS) paths well-separated users.