Information dissemination in MIMO networks

The physical-layer multicast transmission that seeks to deliver the common information messages to the all users simultaneously is becoming more important in wireless systems with demand for various multimedia mobile applications such as Multimedia Broadcast Multicast Services. The spatial randomness of communicating nodes in a wireless network is one of inevitable uncertainty in design and analysis of network information flow and connectivity. In this paper, we characterize local information flow in a stochastic multiple-input multiple-output (MIMO) multicast network where a probe transmitter geobroadcasts common data with sectorized transmission to receivers sitting in a region R. We first put forth a measure of the total amount of common information flow, called the space-time capacity, into R in a spatial random field of receivers. We then derive the space-time capacity into a sectoral region R and the nth nearest ergodic capacity in a Poisson field to characterize the spatial average and ordering of MIMO ergodic capacity achieved by receivers in R. Using the Marčenko-Pastur law, we further assess the asymptotic space-time capacity and the nth nearest ergodic capacity per receive antenna as the antenna numbers tend to infinity. The framework developed in this work enables us to quantify the local information flow in random MIMO wireless networks by averaging both small-scale fading processes on time and large-scale path losses on space.