  In this paper, we study joint power control and scheduling in uplink massive
multiple-input multiple-output (MIMO) systems with randomly arriving data
traffic. We consider both co-located and Cell-Free (CF) Massive MIMO, where the
difference lies in whether the antennas are co-located at the base station or
spread over a wide network area. The data is generated at each user according
to an individual stochastic process. Using Lyapunov optimization techniques, we
develop a dynamic scheduling algorithm (DSA), which decides at each time slot
the amount of data to admit to the transmission queues and the transmission
rates over the wireless channel. The proposed algorithm optimizes the long-term
user throughput under various fairness policies while keeping the transmission
queues stable. Simulation results show that the state-of-the-art power control
schemes developed for Massive MIMO with infinite backlogs can fail to stabilize
the system even when the data arrival rates are within the network capacity
region. Our proposed DSA shows advantage in providing finite delay with
performance optimization whenever the network can be stabilized.
