On the Feasibility of Situational Awareness in Millimeter Wave Massive MIMO Systems

Situational awareness in wireless networks refers to the availability of information on the states of mobile devices and their propagation environments. Recent studies have shown that the position, orientation, and clock offset of a mobile device can be estimated jointly with a map of reflecting or scattering features in the propagation environment based on the link to a single base station. Yet, it is unknown how important system parameters such as the bandwidth, the number of antennas, and the signal-to-noise ratio affect the estimation accuracy and hence the feasibility of situational awareness. We address this open question by studying the Cramér-Rao lower bound of the joint estimation problem. Particularly, we provide an analytical expression for the corresponding Fisher information matrix and inspect the Cram´er-Rao lower bound via numerical simulations. Our results reveal the following insights. First, the reflection loss of objects in the propagation environment has a profound impact on the estimation accuracy of the states of mobile devices and their maps. Second, the massiveness of arrays is a key enabler for accurate state and map estimation and finally, the geometry of the scenario affects the estimation accuracy profoundly.