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

Scheduling for VoLTE: Resource Allocation Optimization and Low-Complexity Algorithms