Sensing-Aided Hybrid Precoding for Efficient Terahertz Wideband Communications in Multiuser High-Data-Rate IoT
Yang Wang, Chuang Yang, Ziyuan Ren, Yanran Sun, Mugen Peng
Abstract
Terahertz (THz) massive MIMO with wideband hybrid precoding has been considered one of the crucial techniques to compensate for the high-path loss in 6G high-data-rate Internet of Things (IoT). However, the beam split in wideband hybrid precoding makes the beam of different subcarriers aiming at different directions, which results in only partial channel state information (CSI) from the users to the BS. The efficiency of the CSI-based terahertz (THz) wideband beamforming scheme which is more efficient than the hardware-based scheme in narrow-band would degrade severely. To address the degradation, in this article, we first propose a sensing-aided THz wideband hybrid precoding which restores the full CSI. Through sensing and deducing the angle-frequency information, we construct a channel-selecting matrix and inverse the full CSI from our complete channel dictionary. Moreover, in order to satisfy the multiuser access requirements in IoT, we also propose dynamic radio frequency (RF) chains and dynamic power allocation schemes to further enhance the performance in multiuser scenarios based on a new precoding perspective in which each RF chain serves only one user. This benefits from the highly sparse THz channel characteristic. The spectral efficiency and energy efficiency are employed to validate that the proposed is efficient. The numerical results demonstrate that our proposed sensing-aided wideband hybrid precoding scheme achieves similar performance to the optimal precoding and much better performance to the true time delay scheme and the full CSI-based scheme.