GMD-Based Hybrid Beamforming for Large Reconfigurable Intelligent Surface Assisted Millimeter-Wave Massive MIMO
Keke Ying, Zhen Gao, Shanxiang Lyu, Yongpeng Wu, Hua Wang, and, Mohamed-Slim Alouini

TL;DR
This paper proposes a GMD-based hybrid beamforming method for RIS-assisted mmWave MIMO systems, improving spectral efficiency and BER performance by exploiting channel sparsity and LoS angles, with a focus on broadband applications.
Contribution
It introduces a novel GMD-based hybrid beamforming scheme for RIS-assisted mmWave MIMO, leveraging channel sparsity and LoS angles to enhance performance.
Findings
Achieves better BER performance than conventional methods.
Utilizes a simultaneous orthogonal match pursuit algorithm for beam selection.
Provides an initial exploration of broadband hybrid beamforming for RIS-assisted systems.
Abstract
Reconfigurable intelligent surface (RIS) is considered to be an energy-efficient approach to reshape the wireless environment for improved throughput. Its passive feature greatly reduces the energy consumption, which makes RIS a promising technique for enabling the future smart city. Existing beamforming designs for RIS mainly focus on optimizing the spectral efficiency for single carrier systems. To avoid the complicated bit allocation on different spatial domain subchannels in MIMO systems, in this paper, we propose a geometric mean decomposition-based beamforming for RIS-assisted millimeter wave (mmWave) hybrid MIMO systems so that multiple parallel data streams in the spatial domain can be considered to have the same channel gain. Specifically, by exploiting the common angular-domain sparsity of mmWave massive MIMO channels over different subcarriers, a simultaneous orthogonal match…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Millimeter-Wave Propagation and Modeling · Indoor and Outdoor Localization Technologies
