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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.