Low-complexity hardware and algorithm for joint communication and sensing

TL;DR

This paper introduces a low-complexity joint communication and sensing algorithm utilizing a hybrid beamforming architecture, achieving high-resolution ToA and AoA estimation with reduced sampling rate and computational complexity, suitable for 6G systems.

Contribution

The paper proposes a novel beamforming architecture and a simplified estimation method that reduces complexity while maintaining high resolution in joint communication and sensing.

Findings

Achieves ToA and AoA estimation performance comparable to fully digital systems.

Reduces sampling rate and computational complexity significantly.

Eliminates the need for 2D/3D joint estimation methods.

Abstract

Joint Communication and Sensing (JCAS) is foreseen as one very distinctive feature of the emerging 6G systems providing, in addition to fast end reliable communication, the ability to obtain an accurate perception of the physical environment. In this paper, we propose a JCAS algorithm that exploits a novel beamforming architecture, which features a combination of wideband analog and narrowband digital beamforming. This allows accurate estimation of Time of Arrival (ToA), exploiting the large bandwidth and Angle of Arrival (AoA), exploiting the high-rank digital beamforming. In our proposal, we separately estimate the ToA and AoA. The association between ToA and AoA is solved by acquiring multiple non-coherent frames and adding up the signal from each frame such that a specific component is combined coherently before the AoA estimation. Consequently, this removes the need to use 2D and 3D joint estimation methods, thus significantly lowering complexity. The resolution performance of the method is compared with that of 2D MUltiple SIgnal Classification (2D-MUSIC) algorithm, using a fully-digital wideband beamforming architecture. The results show that the proposed method can achieve performance similar to a fully-digital high-bandwidth system, while requiring a fraction of the total aggregate sampling rate and having much lower complexity.