Event-Based Beam Tracking with Dynamic Beamwidth Adaptation in Terahertz (THz) Communications

TL;DR

Simulation results show that the proposed beamforming scheme improves average rate performance and reduces the amount of outages caused by the brittle THz misalignment process and the particularly severe path loss in the THz band.

Abstract

Terahertz (THz) communication will be a key enabler for next-generation wireless systems. While THz frequency bands provide abundant bandwidth and extremely high data rates, their effective operation is inhibited by short communication ranges and narrow beams, thus, leading to major challenges pertaining to user mobility, beam alignment, and handover. In particular, there is a strong need for novel beam tracking methods that consider the tradeoff between enhancing the received signal strength via increasing beam directivity, and increasing the coverage probability by widening the beam. In this paper, a multi-objective optimization problem is formulated with the goal of jointly maximizing the expected rate and minimizing the outage probability subject to transmit power and overhead constraints. Subsequently, a novel parameterized beamformer with dynamic beamwidth adaptation is proposed. In addition to the precoder, an event-based beam tracking approach is introduced that efficiently prevents outages caused by beam misalignment and dynamic blockage while maintaining a low pilot overhead. Simulation results show that the proposed beamforming scheme improves average rate performance and reduces the amount of outages caused by the brittle THz misalignment process and the particularly severe path loss in the THz band. Moreover, the proposed event-triggered THz channel estimation approach enables connectivity with minimal overhead and reliable communication at THz bands.

Figures (9)

• Figure 2: Geometry of expected user position vector $\boldsymbol{\hat{p}}_k$, actual position $\boldsymbol{p}_k$ and AoD estimation error $\varepsilon_k$, assuming that the BS is located at the origin.
• Figure 3: Illustration of beam misalignment induced by user mobility.
• Figure 4: Flow diagram showing the tracking algorithm, including event-based pilot transmission and handovers.
• Figure 5: \ref{['fig:pareto_boundary']} Pareto boundary and feasible region of the generally optimized beamformer and the achievable region of the proposed parameterized beamformer, with $R_\mathrm{min}=5$ Gbps, $d=8$ m, and $\sigma_{\tilde{\varepsilon}}=1.5^\circ$. \ref{['fig:beam_pattern']} Beam pattern with optimized parameters corresponding to the three points marked in \ref{['fig:pareto_boundary']} in comparison to the non-robust beam.
• Figure 6: Contour plot of the optimized beamwidth parameter $v$ as a function of distance and AoD deviation $\sigma_{\tilde{\varepsilon}}$, for $\alpha=1$ and $\alpha=0$. Larger values of $v$ lead to a wider beam, while $v=0$ corresponds to the non-robust beamformer.

Theorems & Definitions (2)

• Remark 1
• Remark 2