  Agile beam management is key for providing seamless millimeter wave (mm-wave)
connectivity given the site-specific spatio-temporal variations of the mm-wave
channel. Leveraging non radio frequency (RF) sensor inputs for environment
awareness, e.g. via machine learning (ML) techniques, can greatly enhance
RF-based beam steering. To overcome the lack of diverse publicly available
multi-modal mm-wave datasets for the design and evaluation of such novel beam
steering approaches, we demonstrate our software-defined radio multi-band
mm-wave measurement platform which integrates multi-modal sensors towards
environment-aware beam management.
