We consider scheduling and resource allocation in long-term evolution (LTE) networks across voice over the 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 applicationspecific requirement. 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 scheme, with extremely low complexity. The formulations illustrate the details required to realize resource allocation in an implemented standard. The 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.
Similarly, authors in REF solved the optimization problem for throughput maximization and proposed a heuristic scheme with low complexity.
Scheduling for VoLTE: Resource Allocation Optimization and Low-Complexity Algorithms
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Computer Science Mathematics