Distributed ISAC: Beamforming, Estimation, Learning and More

Unlike single-node ISAC, which is limited in robustness and environmental awareness, Distributed ISAC (DISAC) networks exploit multi-node coordination — across base stations and user devices — to jointly deliver connectivity and multi-perspective sensing. The distributed aspect makes an entire re-design of fundamental transceiver functions necessary. For example, in a DISAC network, the precoder/combiner designs must be coordinated across multiple nodes in rapidly changing environments. In addition, hardware imperfections challenge coherence: antenna calibration scales to a complicated multi-dimensional problem, and multi-node synchronization in time, frequency and phase is challenging, but both aspects need to be addressed to achieve coherence. Distributed settings naturally lead to the challenge of jointly estimating the multipath features associated with multiple user and target channels, which can later be exploited for communication, localization and sensing including imaging. This talk will present recent progress on algorithms and architectures for distributed transceivers that perform sensing, learning, and communication jointly — while remaining robust to hardware impairments, non-ideal propagation, and environmental dynamics.