Vertical Federated Edge Learning with Distributed Integrated Sensing and Communication. (arXiv:2201.08512v1 [eess.SP])

Web: http://arxiv.org/abs/2201.08512

This letter studies a vertical federated edge learning (FEEL) system for
collaborative objects/human motion recognition by exploiting the distributed
integrated sensing and communication (ISAC). In this system, distributed edge
devices first send wireless signals to sense targeted objects/human, and then
exchange intermediate computed vectors (instead of raw sensing data) for
collaborative recognition while preserving data privacy. To boost the spectrum
and hardware utilization efficiency for FEEL, we exploit ISAC for both target
sensing and data exchange, by employing dedicated frequency-modulated …

arxiv communication distributed edge learning sensing