Inverse Scattering Approach to Integration of Communication and Sensing

The development of microwave technology leads to the integration of sensing and communication, i.e., ISAC, with the benefits of resource sharing and co-design. Since sensing passive targets is physically a scattering process, ISAC can be tackled by solving inverse scattering problems (ISPs). This review focuses on ISPs based on orthogonal frequency division multiplexing (OFDM), i.e., communication-centric ISAC. It starts with the introduction of the forward problem, which serves as a foundation for solving ISPs. Moreover, we provide a classification of existing ISAC works based on hardware complexity, algorithmic design, and application scenarios. The requirements, principles, and performance of imaging algorithms are then discussed. Existing ISAC imaging methods primarily focus on conventional approaches. However, the ISPs field has accumulated extensive experience in imaging. Therefore, transferring the well-established techniques from ISPs to the ISAC domain is of great significance. To this end, we propose two methods that adapt ISPs approaches for ISAC imaging: beam-steering learning method and wavenumber domain learning method, which illustrate the potential of integrating ISPs methodologies into ISAC frameworks.