  The paper has two parts. The first one deals with how to use large random
matrices as building blocks to model the massive data arising from the massive
(or large-scale) MIMO system. As a result, we apply this model for distributed
spectrum sensing and network monitoring. The part boils down to the streaming,
distributed massive data, for which a new algorithm is obtained and its
performance is derived using the central limit theorem that is recently
obtained in the literature. The second part deals with the large-scale testbed
using software-defined radios (particularly USRP) that takes us more than four
years to develop this 70-node network testbed. To demonstrate the power of the
software defined radio, we reconfigure our testbed quickly into a testbed for
massive MIMO. The massive data of this testbed is of central interest in this
paper. It is for the first time for us to model the experimental data arising
from this testbed. To our best knowledge, we are not aware of other similar
work.
