Robust methods for LTE and WiMAX dimensioning

TL;DR

This paper develops robust analytic methods for dimensioning LTE and WiMAX networks, addressing the variability in user requirements and providing guarantees on loss probabilities using advanced statistical techniques.

Contribution

It introduces a new dimensioning approach using Edgeworth expansions with error bounds and a concentration inequality-based procedure for conservative estimates.

Findings

Edgeworth expansions improve dimensioning accuracy with performance guarantees.

Gaussian approximation is unreliable for this application.

The proposed methods provide practical tools for network planning under uncertainty.

Abstract

This paper proposes an analytic model for dimensioning OFDMA based networks like WiMAX and LTE systems. In such a system, users require a number of subchannels which depends on their \SNR, hence of their position and the shadowing they experience. The system is overloaded when the number of required subchannels is greater than the number of available subchannels. We give an exact though not closed expression of the loss probability and then give an algorithmic method to derive the number of subchannels which guarantees a loss probability less than a given threshold. We show that Gaussian approximation lead to optimistic values and are thus unusable. We then introduce Edgeworth expansions with error bounds and show that by choosing the right order of the expansion, one can have an approximate dimensioning value easy to compute but with guaranteed performance. As the values obtained are highly dependent from the parameters of the system, which turned to be rather undetermined, we provide a procedure based on concentration inequality for Poisson functionals, which yields to conservative dimensioning. This paper relies on recent results on concentration inequalities and establish new results on Edgeworth expansions.