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.
Highlights
In the coming years, an exponential growth of cellular traffic is expected
Even if traces include both downlink and uplink measurements, the analysis presented here is restricted to the downlink
A data-driven methodology for deriving the Signal-to-Interference-plus-Noise Ratio (SINR)-to-spectral efficiency mapping curves for Long Term Evolution (LTE) downlink on a cell basis based on connection traces has been proposed
Summary
An exponential growth of cellular traffic is expected. a 10-fold increase in mobile data traffic is forecast from 2015 to 2021 [1]. Even if channel capacity is mainly determined by signal quality, it is affected by the radio environment (user speed, propagation channel, etc.), the traffic properties (service type, burstiness, etc.), and the techniques in the different communication layers (multiantenna configuration, interference cancellation, channel coding, radio resource management, etc.) As considering all these factors is extremely difficult, most network planning tools rely on mapping curves relating signal quality to SE (a.k.a. SE curves), generated by link-level simulators [20,21,22]. The main contributions of this work are (a) a data-driven methodology for deriving SE mapping curves from real network measurements, which can be integrated in commercial network planning tools, and (b) a set of SE curves obtained from connection traces collected in two live LTE systems.
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