  Sensing using cellular infrastructure may be one of the defining feature of
sixth generation (6G) wireless systems. Wideband 6G communication channels
operating at higher frequency bands (upper mmWave bands) are better modeled
using clustered geometric channel models. In this paper, we propose methods for
detection of passive targets and estimating their position using communication
deployment without any assistance from the target. A novel AI architecture
called CsiSenseNet is developed for this purpose. We analyze the resolution,
coverage and position uncertainty for practical indoor deployments. Using the
proposed method, we show that human sized target can be sensed with high
accuracy and sub-meter positioning errors in a practical indoor deployment
scenario.
