Queue-Aware Channel-Adapted Scheduling and Congestion Control for Best-Effort Services in LTE Networks

In this paper, we study the performance of long-term evolution (LTE) for various types of channel-adapted scheduling for nonreal-time flows, while an end-to-end congestion control algorithm controls the rate of elastic traffic at the end users. First, we propose a new type of queue-aware channel-adapted scheduling at a base station, and explain how it allocates resources to competing nonreal-time flows where channel conditions are time-varying. We also introduce a new congestion measure function for a minimum cost flow control (MCFC) algorithm in the LTE and call it an individual flow-based congestion measure. We show that using different combinations of channel-adapted scheduling at the base station and congestion control algorithms can lead to major differences in the obtained throughput and fairness for the best-effort traffic. The results clearly show that the transport protocol and scheduling algorithm can cause significant conflict in some situations. We show the advantages of the proposed queue-aware channel-adapted scheduling in performance improvement and we also show that the combination of an MCFC algorithm (in which the new individual flow-based congestion measure is applied), with queue-aware proportional fair scheduling, leads to a better tradeoff between overall throughput and fairness compared with the other studied combinations.