MassiVe MIMO Radio channel- and Learning-based Indoor Passive Localization and Posture Identification for Multiple Humans (V.I.P.)

The aim of the proposed V.I.P. project is to achieve passive localization and posture identification of multiple humans in indoor environment for assisted-living functionalities.  We propose to use the temporal-spatial-delay domain radio channel properties with dedicated design of massive Multiple-Input Multiple-Output (MIMO) topology and configuration for specific physical environment, and use the neural-networks-based learning algorithm recognizing the interactions betwee the human form-factors (body type/shape, posture, motion) and the aforementioned indoor radio channel.  Both simulation and measurement platforms will be built to estimate and measure the radio propagation from the reconfigurable physcial environement, multiple-antenna systems, and human form-factors.