Abstract
The constant evolution in mobile communications networks have led operators to seek new techniques to optimize their mobile networks with the objective of satisfying the expectations of the users. In this way, traditional optimization techniques based on improving radio indicators, have given way to new techniques based on improving the quality of experience (QoE) perceived by users. This paper is focused on analyzing the impact of the adjustment of radio link control (RLC) layer configuration parameters on the QoE perceived by the users of two different types of services. Firstly, an evaluation of the QoE experienced by the user of a real-time video streaming service with respect to the transmission buffer size of the RLC layer in unacknowledged mode (UM) has been carried out. Secondly, the QoE perceived by the user of a file transfer service in relation to the variation of the configuration parameters of the RLC layer in acknowledged mode (AM) has been evaluated. The study, which has been carried out in a simulated cellular environment, has been performed for different system bandwidth values, thus proving the relationship between the QoE perceived by the users, the optimal RLC configuration parameters values and the available bandwidth.
Highlights
This is due to the fact that, by increasing the bandwidth while maintaining the same number of users in the cell, users will have a greater amount of resources to transmit or receive
The analysis has been performed in a Long-Term Evolution (LTE) environment, due to the similarity between the radio link control (RLC) layer in LTE and 5G technologies, the analysis could be reproduced in a 5G scenario
The results obtained in this paper are not directly applicable to 5G, the proposed methodology is valid for improving the quality of experience (QoE) of users of 5G networks
Summary
The introduction of new services that require more and more radio resources and the growth of users’ expectations have led mobile network operators (MNOs) to seek new techniques to optimize their networks. The purpose of the optimization process has been changing, increasingly approaching to users’ perception of the offered services. This change of focus in the goal of network optimization is accentuated with the arrival of the fifth generation (5G) networks [2]. In these networks, with the aim of providing the best possible user experience, a user-centric management approach is proposed [3]. KQIs are a set of metrics that provide information about the service quality at application level, Sensors 2020, 20, 2474; doi:10.3390/s20092474 www.mdpi.com/journal/sensors
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