  5G and beyond networks are expected to support flows with varied
\emph{Quality-of-Service (QoS)} requirements under unpredictable traffic
conditions. Consequently, designing policies ensuring optimal system
utilization in such networks is challenging. Given this, we formulate a
long-term time-averaged scheduling problem that minimizes a weighted function
of packets dropped by the 5G wireless base station. We then present two
policies for this problem. The first is a delay-guaranteed near-optimal policy,
and the second is a delay-guaranteed sub-optimal policy that provides flow
isolation. We perform extensive simulations to understand the performance of
these policies. Further, we study these policies in the presence of a
closed-loop flow rate-control mechanism.
