  Device-Free Localization (DFL) employs passive radio techniques capable to
detect and locate people without imposing them to wear any electronic device.
By exploiting the Integrated Sensing and Communication paradigm, DFL networks
employ Radio Frequency (RF) nodes to measure the excess attenuation introduced
by the subjects (i.e., human bodies) moving inside the monitored area, and to
estimate their positions and movements. Physical, statistical, and
ElectroMagnetic (EM) models have been proposed in the literature to estimate
the body positions according to the RF signals collected by the nodes. These
body models usually employ a single-antenna processing for localization
purposes. However, the availability of low-cost multi-antenna devices such as
those used for WLAN (Wireless Local Area Network) applications and the timely
development of array-based body models, allow us to employ array-based
processing techniques in DFL networks. By exploiting a suitable array-capable
EM body model, this paper proposes an array-based framework to improve people
sensing and localization. In particular, some simulations are proposed and
discussed to compare the model results in both single- and multi-antenna
scenarios. The proposed framework paves the way for a wider use of
multi-antenna devices (e.g., those employed in current IEEE 802.11ac/ax/be and
forthcoming IEEE 802.11be networks) and novel beamforming algorithms for DFL
scenarios.
