  Incorporation of high-rate internet of things (IoT) service into a massive
MIMO framework is investigated. It is revealed that massive MIMO possess the
inherent potential to offer such service provided it knows the channels for all
devices. Our proposed method is to jointly estimate and track the channels of
all devices irrespective of their current activity. Using the dynamical model
for devices' channels evolution over time, optimal and sub-optimal trackers are
developed for coordinated scenario. Furthermore, we introduce a new paradigm
where the BS need not know the pilot access patterns of devices in advance
which we refer to as uncoordinated setup. After motivating this scenario, we
derive the optimal tracker which is intractable. Then, target tracking
approaches are applied to address uncertainties in the measurements and derive
sub-optimal trackers. Our proposed approaches explicitly address the channel
aging problem and will not require downlink paging and uplink access request
control channels which can become bottlenecks in crowded scenarios. The
fundamental minimum mean square error (MMSE) gap between optimal coordinated
and uncoordinated trackers which is defined as price of anarchy is evaluated
and upper-bounded. Stability of optimal trackers is also investigated. Finally,
performance of various proposed trackers are numerically compared.
