  In this paper, we study the joint power control and scheduling in uplink
massive multiple-input multiple-output (MIMO) systems with random data
arrivals. 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 achieves nearly optimal performance on
the long-term user throughput under various fairness policies. Simulation
results show that the DSA can improve the time-average delay performance
compared to the state-of-the-art power control schemes developed for Massive
MIMO with infinite backlogs.
