How user throughput depends on the traffic demand in large cellular networks

TL;DR

This paper derives a theoretical framework linking user throughput to traffic demand in large cellular networks, validated through simulations and real measurements, accounting for network irregularities and load.

Contribution

It introduces a novel analytical approach using ergodic and Palm theory to relate mean user throughput to traffic demand and network geometry, including irregularities.

Findings

Analytical results match simulation data for Poisson network models.

The approach accurately predicts throughput in real network measurements.

Network irregularities and shadowing effects are effectively incorporated.

Abstract

Little's law allows to express the mean user throughput in any region of the network as the ratio of the mean traffic demand to the steady-state mean number of users in this region. Corresponding statistics are usually collected in operational networks for each cell. Using ergodic arguments and Palm theoretic formalism, we show that the global mean user throughput in the network is equal to the ratio of these two means in the steady state of the "typical cell". Here, both means account for double averaging: over time and network geometry, and can be related to the per-surface traffic demand, base-station density and the spatial distribution of the SINR. This latter accounts for network irregularities, shadowing and idling cells via cell-load equations. We validate our approach comparing analytical and simulation results for Poisson network model to real-network cell-measurements.