Sensing Mutual Information with Random Signals in Gaussian Channels

Lei Xie1; Fan Liu2; Zhanyuan Xie3; Zheng Jiang3; Shenghui Song1

10.1109/ICC51166.2024.10622618

2024-06-13

1550-3607

978-1-7281-9055-6

ICC 2024 - IEEE International Conference on Communications

9-13 June 2024

Denver, CO, USA

Sensing performance is typically evaluated by classical metrics, such as Cramer-Rao bound and signal- to-clutter-plus-noise ratio. The recent development of the integrated sensing and communication (ISAC) framework motivated the efforts to unify the metric for sensing and communication, where researchers have proposed to utilize mutual information (MI) to measure the sensing performance with deterministic signals. However, the need to communicate in ISAC systems necessitates the use of random signals for sensing applications and the closed-form evaluation for the sensing mutual information (SMI) with random signals is not yet available in the literature. This paper investigates the SMI and precoder design for sensing applications with random signals. For that purpose, we first derive the closed-form expression for the SMI with random signals by utilizing random matrix theory. The result reveals some interesting physical insights regarding the relation between the SMI with deterministic and random signals. The derived SMI is then utilized to optimize the precoder by leveraging a manifold-based optimization approach. The accuracy of the theoretical analysis and the effectiveness of the proposed precoder design method are validated by simulation results.

其他

1.The Hong Kong University of Science and Technology, Hong Kong
2.Southern University of Science and Technology, China
3.China Telecom Research Institute, China

Lei Xie,Fan Liu,Zhanyuan Xie,et al. Sensing Mutual Information with Random Signals in Gaussian Channels[C],2024.