  Integrated sensing and communication (ISAC) has opened up numerous
game-changing opportunities for future wireless systems. In this paper, we
develop a novel scheme that utilizes orthogonal frequency division multiplexing
(OFDM) pilot signals to sense the electromagnetic (EM) property of the target
and thus identify the materials of the target. Specifically, we first establish
an EM wave propagation model with Maxwell equations, where the EM property of
the target is captured by a closed-form expression of the channel. We then
build the mathematical model for the relative permittivity and conductivity
distribution (RPCD) within a predetermined region of interest shared by
multiple base stations (BSs). Based on the EM wave propagation model, we
propose an EM property sensing method, in which the RPCD can be reconstructed
from compressive sensing techniques that exploits the joint sparsity structure
of the EM property vector. We then develop a fusion algorithm to combine data
from multiple BSs, which can enhance the reconstruction accuracy of EM property
by efficiently integrating diverse measurements. Moreover, the fusion is
performed at the feature level of RPCD and features low transmission overhead.
We further design the pilot signals that can minimize the mutual coherence of
the equivalent channels and enhance the diversity of incident EM wave patterns.
Simulation results demonstrate the efficacy of the proposed method in achieving
high-quality RPCD reconstruction and accurate material classification.
