Electromagnetic Property Sensing: A New Paradigm of Integrated Sensing and Communication

Integrated sensing and communication (ISAC) has opened up numerous game-changing opportunities for realizing future wireless systems. In this paper, we develop a novel material sensing scheme that utilizes OFDM pilot signals in ISAC systems to sense the electromagnetic (EM) property and identify the material of the target. Specifically, we first establish an end-to-end EM propagation model by means of Maxwell equations, where the electrical properties of the material are captured by a closed-form expression for the non-line-of-sight (NLOS) channel, incorporating the Lippmann-Schwinger equation and the method of moments (MOM) for discretization. We then model the relative permittivity and conductivity distribution (RPCD) within a specified detection region. Based on the sensing model, we introduce a multi-frequency-based material sensing method by which the RPCD can be reconstructed from compressive sensing techniques that exploits the joint sparsity structure of the contrast source vector. To improve the sensing accuracy, we design a beamforming strategy from the communications transmitter based on the Born approximation, which can minimize the mutual coherence of the sensing matrix. The optimization problem is cast in terms of the Gram matrix and is solved iteratively to obtain the optimal beamforming matrix. Simulation results demonstrate the efficacy of the proposed method in achieving high-quality RPCD reconstruction and accurate material classification. Furthermore, improvements in RPCD reconstruction quality and material classification accuracy are observed with increased signal-to-noise ratio (SNR) or reduced target-transmitter distance.