Abstract
Subarray-based hybrid beamforming communication systems are a cost- and power-efficient architectural solution to realize massive multiple-input multiple-output (MIMO) systems. To estimate the required channel state information (CSI) current research focuses on beam training algorithms, which suffer from long estimation times and require precise system calibration. In order to overcome these problems, two channel estimation algorithms in combination with suitable beamforming algorithms are proposed. The presented algorithms are based on sparse array measurements, where only one antenna per subarray is active during the estimation process. This allows for the reconstruction of the complex MIMO channel matrix by performing multiple sparse array measurements. Channel estimation algorithms, which drastically reduce the channel estimation time are proposed in this letter. Their high performance is proven in small cell communication measurements around 28 GHz.
Highlights
H YBRID beamforming systems split the beamforming process into a digital and analog beamforming network enabling a cost and energy-efficient implementation of massive multiple-input multiple-output (MIMO) communication systems [1]
As the large antenna spacing of the active antennas for the sparse array measurement leads to grating lobes within the antenna array characteristic, ambiguities for the main propagation directions are present in the beam pattern C s(φ)
In contrast to the Multiple Sparse Array Measurements (MSAM) algorithm, a calibration in amplitude and phase between the parallel Rx chains is needed. This calibration is required for an exhaustive search and hierarchical beam training algorithms, as an uncalibrated system would lead to a distorted beam pattern
Summary
H YBRID beamforming systems split the beamforming process into a digital and analog beamforming network enabling a cost and energy-efficient implementation of massive multiple-input multiple-output (MIMO) communication systems [1]. Current research on channel estimation for hybrid beamforming systems in the centimeter-wave (cmWave) and millimeter-wave (mmWave) region focuses on beam training algorithms. These algorithms try to find the dominant spatial propagation paths characterized by pairs of angles of departure (AoDs) at the transmitter (Tx) and angles of arrival (AoAs) at the receiver (Rx). Beside the hierarchical beam training algorithms, the sparse nature of the channel can be exploited at higher mmWave frequencies by utilizing compressed sensing techniques [11]–[16]. The focus is on the new radio n257-band around 28 GHz specified by the 3rd generation partnership project (3GPP) In this band the presented measurements by Rappaport et al [17] show an average of 4.7 multipath components between a transmitter and a receiver.
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