Integrated Sensing and Communications With Mixed Fields Using Transmit Beamforming

Abstract

Integrated sensing and communications (ISAC) is an important enabling technology for the next-generation wireless systems. Owing to the use of large-scale antenna arrays and/or high carrier frequencies, the communications user and the target may follow different propagation models. However, most existing works assume either far-field or near-field propagation models for both communications and sensing. In this letter, a realistic case is considered when the communications user and the target are in different fields. New beamforming designs are proposed to optimize the sensing performance considering a bi-static setting. Specifically, the sensing signal-to-clutter-plus-noise ratio (SCNR) is optimized, and a generalized iterative algorithm is proposed to solve the optimization problem. Numerical results show the effects of model mismatch between near-field and far-field, antenna size and communications channel on the sensing performance.