Tri-Hybrid Beamforming Design for integrated Sensing and Communications

TL;DR

This paper proposes a tri-hybrid beamforming design for integrated sensing and communications, optimizing performance while considering power and physical constraints, and demonstrating improved energy efficiency through an efficient iterative algorithm.

Contribution

It introduces a novel tri-hybrid beamforming framework for ISAC, formulating a multi-objective optimization and developing a low-complexity iterative solution.

Findings

Enhanced spatial gain and energy efficiency.

Reduced beam alignment capability compared to traditional architectures.

Fast convergence of the proposed iterative algorithm.

Abstract

Tri-hybrid beamforming architectures have been proposed to enable energy-efficient communications systems in extra-largescale antenna arrays using low-cost programmable metasurface antennas. We study the tri-hybrid beamforming design for integrated sensing and communications (ISAC) to improve both communications and sensing performances. Specifically, we formulate a multi-objective optimization problem that balances communications signal-to-noise ratio (SNR) and the sensing power at a target direction, subject to constraints on the total power consumption and physical limitations inherent to the trihybrid beamforming architecture. We develop an efficient iterative algorithm in which the variables are updated in a closed form at each iteration, leading to a low-complexity and fast-execution design. Numerical results show that the tri-hybrid architecture improves spatial gain and energy efficiency, though with reduced beam alignment capability compared to conventional hybrid beamforming architectures.