MODIFIED METHOD FOR ASSESSING THE IMPACT OF NETWORK PARAMETERS ON SERVICE QUALITY IN LTE MOBILE NETWORKS

DOI: 10.31673/2786-8362.2025.026359

Abstract

LTE networks continue to be the primary
infrastructure for mobile access, providing high-volume multimedia traffic and supporting latency-sensitive
services. Despite the active introduction of 5G technologies, LTE dominates in many regions in terms of
coverage and network load, which necessitates a detailed analysis of the parameters that determine the
quality of service for users. One of the key factors affecting network performance is the number of active
users and the transmission power of the base station. Changes in these parameters directly affect the
operation of the resource scheduler, retransmission mechanisms, and queue formation at the RLC level,
which determines packet delay in the downlink and uplink paths. This is especially critical for video
streaming, where playback stability and the final quality of the user experience depend on it. Existing
studies either generalize the impact of network parameters or do not take into account the nonlinear nature
of delay growth and dependence on base station power, which creates a need to develop an approach that
allows quantifying the impact of these parameters, identifying critical operating modes, and predicting
service quality degradation. The article proposes an approach to assessing the impact of radio network
parameters such as the number of active users and base station power on latency metrics in LTE networks,
with a focus on video streaming services. The research was conducted in the OMNeT++ environment; the
results are summarized in the form of approximation models, determination of the critical load zone, and
an integral quality index for video services. The article proposes a modified evaluation method that
combines a power correction factor and the determination of a quality degradation threshold point. The
improved method provides a 22-25% increase in the accuracy of determining the critical load point
compared to the existing network, and also reduces the error in predicting delay characteristics in high-load
modes by an average of 3-5%.
Keywords: LTE, delay, RLC, OMNeT++, network load, polynomial approximation, critical point,
video service quality, QoS/QoE

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