# QoE Optimization in a Live Cellular Network through RLC Parameter Tuning
## 1 Introduction
To perform the optimization, a controller based on [PERSON]'s method (TM) has been used. Although TM has been proposed in the literature to perform optimization tasks for radio network parameters [18], to the best of our knowledge, this is the first work to use TM for QoE optimization in mobile networks. In this sense, this paper extends the contribution of [17] in which an assessment of the impact of the RLC layer configuration on QoE is presented. The main contributions of this paper are detailed as follows. * First, unlike in the state of the art methods, where the main objective is to conduct a sensitivity study of how RLC behaves and its different modes of operation, this paper proposes the use of an optimizer based on TM to automatically adjust the configuration parameters of RLC in both operating modes of AM and UM. * Second, the optimization proposed in this article focuses on the improvement of the QoE perceived by network users. Despite the great impact of the RLC layer on the reliable transmission of data and, therefore, on the QoE perceived by users, the optimization of the QoE based on the adjustment of the RLC configuration parameters has not been addressed in the state of the art approaches. In this paper, the proposed optimization scheme provides the values of the configuration parameters that maximize the QoE perceived by a user for both RLC operating modes of AM and UM. Moreover, the optimization has been carried out for different bandwidth values, establishing a relationship between the RLC configuration parameters, the bandwidth value available in the network, and the obtained QoE. * Third, in order to evaluate the proposed optimization algorithm, a proof of concept has been carried out. This proof of concept includes a set of tests using two different scenarios. On the one hand, a simulated scenario has been used to analyze the QoE improvements achieved by the automatic RLC layer configuration parameter adjustment. On the other hand, a long-term evolution (LTE) testbed (see Appendix A) has been considered to evaluate the proposed algorithm in a real environment. Althoughthe environments used in the proof of concept correspond to LTE environments, the optimization algorithm proposed in this paper could be used in 5G environments due to the great similarity between the RLC layers of both LTE and 5G technologies [19]. The remainder of this paper is organized as follows. In Section 2, a summary of the RLC layer operation as it is described in the Third Generation Partnership Project (3 GPP) is provided. In order to understand the effect caused by a bad configuration of the RLC parameters on the applications that make use of the TCP protocol, as in the case of a file transmission service, it is important to know how the TCP congestion control algorithm works. In this sense, Section 3 describes the main functionalities of the TCP layer, with special emphasis on the study of congestion control. The main characteristics, as well as the metrics used to evaluate the QoE in the different types of services, are defined in Section 4. In Section 5, [PERSON]'s method, which is used to perform the optimization of the QoE, is presented. The result of the optimization tasks carried out in the simulator and in the real network are shown in Section 6. Finally, Section 7 presents the conclusions inferred from the results.