  We consider scheduling and resource allocation in long-term evolution (LTE)
networks across voice over LTE (VoLTE) and best-effort data users. The
difference between these two is that VoLTE users get scheduling priority to
receive their required quality of service. As we show, strict priority causes
data services to suffer. We propose new scheduling and resource allocation
algorithms to maximize the sum- or proportional fair (PF) throughout amongst
data users while meeting VoLTE demands. Essentially, we use VoLTE as an example
application with both a guaranteed bit-rate and strict application-specific
requirements. We first formulate and solve the frame-level optimization problem
for throughput maximization; however, this leads to an integer problem coupled
across the LTE transmission time intervals (TTIs). We then propose a TTI-level
problem to decouple scheduling across TTIs. Finally, we propose a heuristic,
with extremely low complexity. The formulations illustrate the detail required
to realize resource allocation in an implemented standard. Numerical results
show that the performance of the TTI-level scheme is very close to that of the
frame-level upper bound. Similarly, the heuristic scheme works well compared to
TTI-level optimization and a baseline scheduling algorithm. Finally, we show
that our PF optimization retains the high fairness index characterizing
PF-scheduling.
