Digital Twin Assisted Beamforming Design for Integrated Sensing and Communication Systems

TL;DR

This work tackles joint beamforming design for MIMO ISAC systems under sensing-channel uncertainty by leveraging a static digital twin of the environment. The authors formulate an optimization to maximize sensing SNR while enforcing a minimum communication SINR, and develop baseline methods using full sensing-channel knowledge and LoS directions. The core contribution is a digital-twin–aided approach that uses ray-traced, partial path gains and directions to identify the dominant partial path for sensing, enabling near-optimal SNR performance in both LoS- and NLoS-dominant areas. Simulations on high-fidelity ray-traced data show the proposed method approaches the genie upper bound and satisfies the communication requirements, illustrating the practical value of digital twins for ISAC in realistic settings.

Abstract

This paper explores a novel research direction where a digital twin is leveraged to assist the beamforming design for an integrated sensing and communication (ISAC) system. In this setup, a base station designs joint communication and sensing beamforming to serve the communication user and detect the sensing target concurrently. Utilizing the electromagnetic (EM) 3D model of the environment and ray tracing, the digital twin can provide various information, e.g., propagation path parameters and wireless channels, to aid communication and sensing systems. More specifically, our digital twin-based beamforming design first leverages the environment EM 3D model and ray tracing to (i) predict the directions of the line-of-sight (LoS) and non-line-of-sight (NLoS) sensing channel paths and (ii) identify the dominant one among these sensing channel paths. Then, to optimize the joint sensing and communication beam, we maximize the sensing signal-to-noise ratio (SNR) on the dominant sensing channel component while satisfying a minimum communication signal-to-interference-plus-noise ratio (SINR) requirement. Simulation results show that the proposed digital twin-assisted beamforming design achieves near-optimal target sensing SNR in both LoS and NLoS dominant areas, while ensuring the required SINR for the communication user. This highlights the potential of leveraging digital twins to assist ISAC systems.

Figures (4)

• Figure 1: This figure presents the key idea of leveraging the digital twin to design the joint communication and sensing beamforming. The digital twin can provide partial channel information to guide the beamforming.
• Figure 2: This figure shows the geometry layout of the adopted indoor scenario. The sensing target is placed in the area annotated in orange. The communication user grid (annotated in red) covers the entire indoor space.
• Figure 3: This figure presents the beam patterns of the sensing and the communication beams obtained by the proposed digital twin approach. The main lobes of sensing and communication beams point toward the sensing target direction. The sensing beam forms a null at the direction of the communication user to alleviate interference.
• Figure 4: This figure presents the CDF of the sensing SNR with the minimum communication SINR of 10 dB. The proposed digital twin-aided approach achieves near-optimal performance compared to the genie-aided approach, which has full channel knowledge in both the LoS dominant and NLoS dominant areas.