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Gridless Channel Estimation for Hybrid mmWave MIMO Systems via Tensor-ESPRIT Algorithms in DFT Beamspace

Jianshu Zhang, Damir Rakhimov, Martin Haardt

2021IEEE Journal of Selected Topics in Signal Processing55 citationsDOI

Abstract

In this paper, we present a gridless channel estimation algorithm for a hybrid millimeter wave (mmWave) MIMO-OFDM system assuming a frequency-selective channel. The proposed algorithm is based on the Tensor-ESPRIT in DFT beamspace algorithm framework. First, we derive the R -dimensional (R -D) Standard/Unitary Tensor-ESPRIT in DFT beamspace framework and its analytic performance. We show that ESPRIT-type algorithms in a reduced-dimensional DFT beamspace can provide a significant performance gain over ESPRIT-type algorithms in full DFT beamspace and in element space under mild conditions. Afterwards, we develop a gridless channel estimation algorithm that is based on 3-D Tensor-ESPRIT in DFT beamspace algorithms. Numerical simulation results show that the proposed channel estimation algorithm can provide accurate channel estimates using only a few training resources.

Topics & Concepts

AlgorithmChannel (broadcasting)Tensor (intrinsic definition)Computer scienceMIMOMathematicsTelecommunicationsGeometryAdvanced MIMO Systems OptimizationMillimeter-Wave Propagation and ModelingAdvanced Wireless Communication Techniques