Offloading in Heterogeneous Networks: Modeling, Analysis, and Design Insights

TL;DR

This paper develops a comprehensive model for heterogeneous networks with multiple RATs and tiers, analyzing offloading strategies to optimize system performance and revealing that optimal offloading fractions vary depending on the performance metric.

Contribution

It introduces a tractable, multi-tier, multi-RAT model with Poisson point process deployment, providing insights into optimal offloading strategies for different performance objectives.

Findings

Optimal offloading fractions differ for SINR and rate coverage.

The model captures the impact of deployment density, power, and bandwidth on offloading.

Guidelines for tuning offloading weights to improve network performance.

Abstract

Pushing data traffic from cellular to WiFi is an example of inter radio access technology (RAT) offloading. While this clearly alleviates congestion on the over-loaded cellular network, the ultimate potential of such offloading and its effect on overall system performance is not well understood. To address this, we develop a general and tractable model that consists of $M$ different RATs, each deploying up to $K$ different tiers of access points (APs), where each tier differs in transmit power, path loss exponent, deployment density and bandwidth. Each class of APs is modeled as an independent Poisson point process (PPP), with mobile user locations modeled as another independent PPP, all channels further consisting of i.i.d. Rayleigh fading. The distribution of rate over the entire network is then derived for a weighted association strategy, where such weights can be tuned to optimize a particular objective. We show that the optimum fraction of traffic offloaded to maximize $\SINR$ coverage is not in general the same as the one that maximizes rate coverage, defined as the fraction of users achieving a given rate.