Hybrid 3D Beamforming Relying on Sensor-Based Training and Channel Estimation for Reconfigurable Intelligent Surface Aided TeraHertz MIMO systems

TL;DR

This paper introduces a hybrid 3D beamforming approach for RIS-aided THz MIMO systems, utilizing sensor-based training and channel estimation to enhance spectral efficiency and beamforming accuracy in high-frequency, high-pathloss environments.

Contribution

It proposes a novel hybrid 3D beamformer with sensor-based training, a Precise Beamforming Algorithm, and new channel orthogonality conditions for RIS-aided THz MIMO systems.

Findings

Accurate channel estimation achieved with low complexity.

Significant spectral efficiency improvements demonstrated.

Enhanced beamforming accuracy despite positioning errors.

Abstract

Terahertz (THz) systems have the benefit of high bandwidth and hence are capable of supporting ultra-high data rates, albeit at the cost of high pathloss. Hence they tend to harness high-gain beamforming. Therefore a novel hybrid 3D beamformer relying on sophisticated sensor-based beam training and channel estimation is proposed for Reconfigurable Intelligent Surface (RIS) aided THz MIMO systems. A so-called array-of-subarray based THz BS architecture is adopted and the corresponding sub-RIS structure is proposed. The BS, RIS and receiver antenna arrays of the users are all uniform planar arrays (UPAs). The Ultra-wideband (UWB) sensors are integrated into the RIS and the user location information obtained by the UWB sensors is exploited for channel estimation and beamforming. Furthermore, the novel concept of a Precise Beamforming Algorithm (PBA) is proposed, which further improves the beam-forming accuracy by circumventing the performance limitations imposed by positioning errors. Moreover, the conditions of maintaining the orthogonality of the RIS-aided THz channel are derived in support of spatial multiplexing. The closed-form expressions of the near-field and far-field path-loss are also derived. Our simulation results show that the proposed scheme accurately estimates the RIS-aided THz channel and the spectral efficiency is much improved, despite its low complexity. This makes our solution eminently suitable for delay-sensitive applications.