Dynamic-Subarray With Fixed Phase Shifters for Energy-Efficient Terahertz Hybrid Beamforming Under Partial CSI

Terahertz (THz) communications are regarded as a pillar technology for the 6G systems, by offering multi-ten-GHz bandwidth. To overcome the huge propagation loss, THz ultra-massive MIMO systems with hybrid beamforming are proposed to offer high array gain. Notably, the adjustable phase shifters considered in most existing hybrid beamforming studies are power-hungry and difficult to realize in the THz band. Moreover, due to the ultra-massive antennas, full channel-state-information (CSI) is challenging to obtain. To address these practical concerns, in this paper, an energy-efficient dynamic-subarray with fixed phase shifters (DS-FPS) architecture is proposed for THz hybrid beamforming. To compensate for the spectral efficiency loss caused by the fixed phase of FPS, a switch network is inserted to enable dynamic connections. In addition, by considering the partial CSI, we propose a row-successive-decomposition (RSD) algorithm to design the hybrid beamforming matrices for DS-FPS. A row-by-row (RBR) algorithm is further proposed to reduce the computational complexity. Extensive simulation results show that, the proposed DS-FPS architecture with the RSD and RBR algorithms achieves much higher energy efficiency than the existing architectures. Moreover, the spectral efficiency of the DS-FPS architecture with the proposed algorithms is robust to the CSI error.

Automated summary

In this paper, an energy-efficient dynamic-subarray with fixed phase shifters (DS-FPS) architecture is proposed for terahertz hybrid beamforming, which compensates for the spectral efficiency loss caused by the fixed phase of FPS through a switch network and designs the hybrid beamforming matrices using a row-successive-decomposition (RSD) algorithm. A row-by-row (RBR) algorithm is further proposed to reduce computational complexity. Extensive simulation results show that the proposed DS-FPS architecture with the RSD and RBR algorithms achieves higher energy efficiency and robustness to CSI error compared to existing architectures.