# QoE Optimization in a Live Cellular Network through RLC Parameter Tuning
## 7 Conclusions  
This paper presents a QoE optimization algorithm based on the adjustment of the RLC layer configuration. This algorithm has been evaluated using two types of services with different characteristics: on the one hand, a real-time video streaming service; on the other hand, a file transfer service. These two services usually run on different RLC layer operation modes. The optimization process of these two services has been carried out in a simulated environment. Moreover, the optimization of the QoE perceived by the user of a file transfer service has been performed in a real environment. The RLC layer configuration, both in AM and UM, has a great impact on the losses and the latency experienced by the sent packets. A correct adjustment of the configuration parameters has been studied in these two RLC modes: the transmission buffer size in the RLC UM case and the t-StatusProhibit and t-PollRetransmit timers in the RLC AM case, providing a balance between the losses and the delays suffered by these packets and leading to an improvement in the QoE perceived by the users of the services analyzed. The controller used to carry out the optimization process provides the values that should be adopted for the RLC configuration parameters to maximize the QoE perceived by the user. To this end, the controller only needs to know the configuration parameters' initial search range of values. The optimization process has been performed for different values of bandwidth available in the system, thus proving that the optimal values of the configuration parameters and the maximum QoE experienced by the user are related to the scenario load conditions. The tests carried out in the real network (UMAHetNet) have served to verify the correct functioning of the optimization algorithm in a commercial network, confirming the possibility of optimizing the QoE perceived by users of a file transfer service; in this case, by adjusting the RLC layer in AM mode. In scenarios in which users make use of more than one service at the same time, if these services were carried by different data radio bearers (DRBs), the QoE optimization of the services should be performed separately. Thus, it would be necessary to select a different configuration for each RLC entity associated with a DRB. This selection of RLC parameters would be performed based on what has been learned by running the proposed optimization algorithm in different scenarios and using different services. The algorithm presented in this paper can be used as an input to a decision support system for RLC layer configuration. One of the main lines of future work is the development of an algorithm that is capable of automatically adapting to changes in the scenario and dynamically modifying the RLC layer configuration. Conceptualization, J.M., L.d.-l.-B. and D.P. ; methodology, J.M., L.d.-l.-B. and D.P. ; software, J.M. ; validation, J.M., L.d.-l.-B. and D.P. ; formal analysis, J.M. and L.d.-l.-B. ; investigation, J.M. ; resources, R.B. ; data curation, J.M. ; writing--original draft preparation, J.M. ; writing--  
Figure 11: Real environment—E2E throughput optimization. review and editing, J.M., I.d.-l.-B., D.P. and R.B. ; visualization, J.M. ; supervision, L.d.-l.-B. and R.B. ; project administration, R.B. ; funding acquisition, R.B. All authors have read and agreed to the published version of the manuscript. **Funding:** This work has been partially funded by the European Union's Horizon 2020 research and innovation program under grant agreement No. 644399 (MONROE) through a second open call project (eSON), by the Junta de Andalucia and FEDER in the framework of the project MUSE--\"Massive USer Experience Assessment and Prediction for Mobile Networks\" (Ref. UMA-CEIATECH-13, \"Proyecto singular de actuaciones de transferencia del conocimiento Campus Excelencia Internacional Andalucia TECH. Ecosistema innovador con inteligencia artificial para Andalucia 2025\"), and by the Spanish Ministry of Science, Innovation, and Universities under grant agreement FPU18/04786.