Sensing-Aided Hybrid Precoding for Efficient Terahertz Wideband
Communications in Multi-User High-Data-Rate IoT
Abstract
Terahertz (THz) massive MIMO with wideband hybrid precoding has been
considered one of the crucial techniques to compensate 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
sub-carriers aim at different directions, which results in only partial
channel state information (CSI) from the users to the base station. The
efficiency of the CSI-based THz wideband beamforming scheme which is
more efficient than the hardware-based scheme in the narrow band would
degrade severely. To address the degradation, in this paper, we firstly
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
multi-user access requirements in IoT, we also propose dynamic RF chains
and dynamic power allocation schemes to further enhance the performance
in multi-user scenario based on a new precoding perspective in which
each RF chains 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.