  In beam-based massive multiple-input multiple-output systems, signals are
processed spatially in the radio-frequency (RF) front-end and thereby the
number of RF chains can be reduced to save hardware cost, power consumptions
and pilot overhead. Most existing work focuses on how to select, or design
analog beams to achieve performance close to full digital systems. However,
since beams are strongly correlated (directed) to certain users, the selection
of beams and scheduling of users should be jointly considered. In this paper,
we formulate the joint user scheduling and beam selection problem based on the
Lyapunov-drift optimization framework and obtain the optimal scheduling policy
in a closed-form. For reduced overhead and computational cost, the proposed
scheduling schemes are based only upon statistical channel state information.
Towards this end, asymptotic expressions of the downlink broadcast channel
capacity are derived. To address the weighted sum rate maximization problem in
the Lyapunov optimization, an algorithm based on block coordinated update is
proposed and proved to converge to the optimum of the relaxed problem. To
further reduce the complexity, an incremental greedy scheduling algorithm is
also proposed, whose performance is proved to be bounded within a constant
multiplicative factor. Simulation results based on widely-used spatial channel
models are given. It is shown that the proposed schemes are close to optimal,
and outperform several state-of-the-art schemes.
