Scenario-Based Configuration Refinement for High-Load Cellular Networks: An Operator View

Abstract

With the rapid growth of users and sustained network demands powered by different industries, the quality of service (QoS) of the cellular network is affected by network traffic and computing loads. The current solutions of QoS improvement in academia focus on the fundamental algorithms within the physical and medium access control (MAC) layer. However, traffic features of various scenarios extracted from field data are rarely addressed for practical network configuration refinement. In this paper, we identify significant indicators of high traffic load cells according to the field data provided by telecommunication operators. Then, we propose the analysis flow of high traffic load cells with basic principles of network configuration refinement for QoS improvement. To demonstrate the proposed analysis flow and the refinement principles, we consider three typical scenarios of high traffic load cells, including high population density, emergency, and high-speed mobility. For each scenario, we discuss traffic features with field data. The corresponding performance evaluation demonstrates that the proposed principle can significantly enhance the network performance and user experience in terms of access success rate, downlink data rate, and number of high traffic load cells.