A Unified 3D Beam Training and Tracking Procedure for Terahertz Communication

TL;DR

This paper introduces a comprehensive 3D beam training and tracking method for THz communication systems, addressing challenges of high propagation loss and beam alignment with novel array architecture and low-complexity algorithms.

Contribution

It proposes a unified 3D beam training and tracking framework with a novel array design and low-complexity algorithms tailored for THz communication.

Findings

Enhanced signal coverage and beam gain with QUPA architecture

Reduced beam squint loss in THz beamforming

Superior performance over benchmark methods in simulations

Abstract

Terahertz (THz) communication is considered as an attractive way to overcome the bandwidth bottleneck and satisfy the ever-increasing capacity demand in the future. Due to the high directivity and propagation loss of THz waves, a massive MIMO system using beamforming is envisioned as a promising technology in THz communication to realize high-gain and directional transmission. However, pilots, which are the fundamentals for many beamforming schemes, are challenging to be accurately detected in the THz band owing to the severe propagation loss. In this paper, a unified 3D beam training and tracking procedure is proposed to effectively realize the beamforming in THz communications, by considering the line-of-sight (LoS) propagation. In particular, a novel quadruple-uniform planar array (QUPA) architecture is analyzed to enlarge the signal coverage, increase the beam gain, and reduce the beam squint loss. Then, a new 3D grid-based (GB) beam training is developed with low complexity, including the design of the 3D codebook and training protocol. Finally, a simple yet effective grid-based hybrid (GBH) beam tracking is investigated to support THz beamforming in an efficient manner. The communication framework based on this procedure can dynamically trigger beam training/tracking depending on the real-time quality of service. Numerical results are presented to demonstrate the superiority of our proposed beam training and tracking over the benchmark methods.