Obtaining More Realistic Cross-Layer QoS Measurements: A VoIP over LTE Use Case

We introduce a real-time experimentation testbed in this paper which enables more realistic analysis of quality of service (QoS) in LTE networks. This testbed is envisioned for the improvement of QoS and quality of experience (QoE) through the experimentation with real devices, services, and radio configurations. Radio configurations suggested in the literature typically arise from simulations; the testbed provides a real and controlled testing environment where such configurations can be validated. The added value of this testbed goes a long way not only in the provision of more realistic results but also in the provision of QoS and QoE cross-layer measurements through the correlation of information collected at different layers: from service and IP levels to radio and protocol parameters. Analyzing the interlayer dependencies will allow us to identify optimal settings for the radio access network and service parameters. This information can be used to suggest new cross-layer optimizations to further improve quality of experience of mobile subscribers. As a use case, we examine VoIP service over LTE, which is currently an open issue. 1. Introduction The enhancement of QoS in a sustainable manner is a critical goal for network operators as management tasks are becoming increasingly complex. Although some initial efforts have been carried out by the standardization bodies, there is still a significant gap to be covered in QoS and also in QoE optimization. Actually, current efforts towards improving QoS and QoE are typically based on estimations derived from costly drive test campaigns. Furthermore, involvement of human expertise is required to manually tune network configurations. On the other hand, most of the service and network configurations available in the literature are derived from simulations [1–6]. As is widely known, in the process of modeling communication systems to simulate them, some details may be missed, and thus, misleading results may be derived. For example, it is very common to find that the consumption of control resources is ignored when evaluating different scheduling methods. In this context, providing optimized network configurations based on measurements obtained directly from the subscribers' terminals and correlated with the information collected at the network will pave the way for a reduction of costs and more accurate tuning of network operation from the point of view of the QoS perceived by final users. Moreover, as stated by standards organizations (SDOs) or alliances with the participation of network operators such as