Estimating Spectral Efficiency Curves from Connection Traces in a Live LTE Network

Abstract

In cellular networks, spectral efficiency is a key parameter when designing network infrastructure. Despite the existence of theoretical model for this parameter, experience shows that real spectral efficiency is influenced by multiple factors that greatly vary in space and time and are difficult to characterize. In this paper, an automatic method for deriving the real spectral efficiency curves of a Long Term Evolution (LTE) system on a per-cell basis is proposed. The method is based on a trace processing tool that makes the most of the detailed network performance measurements collected by base stations. The method is conceived as a centralized scheme that can be integrated in commercial network planning tools. Method assessment is carried out with a large dataset of connection traces taken from a live LTE system. Results show that spectral efficiency curves largely differ from cell to cell.

Encrypted Traffic Classification Based on Unsupervised Learning in Cellular Radio Access Networks

“…Their ability to generate new indicators different from counters provided by vendors is extremely valuable for operators [24]. For instance, traces can be used in network planning to derive spectral efficiency curves required in cellular planning and simulation [25] or the spatiotemporal distribution of radio resources in a live network [26]. Likewise, traces can be used in the operational stage to tune network parameters (e.g., link adaptation offset [27], antenna tilt angle [28] or inter-system handover margin [29]) or find the root cause of problems (e.g., dropped connections [30]).…”