Dynamic Channel Bonding in Spatially Distributed High-Density WLANs

TL;DR

This paper analyzes the impact of dynamic channel bonding on throughput and fairness in high-density WLANs, introducing an analytical framework and evaluating different policies through simulations.

Contribution

It presents a novel CTMN-based analytical framework for DCB in spatially distributed WLANs and evaluates adaptive policies for improved fairness and throughput.

Findings

Wider channels generally increase individual throughput.

Unfairness can occur with maximum channel width selection.

Adaptive stochastic channel width policies can improve fairness and throughput.

Abstract

In this paper, we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high-density wireless local area networks (WLANs). First, we present an analytical framework based on continuous-time Markov networks (CTMNs) for depicting the behavior of different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier sense range of each other. Then, we assess the performance of DCB in high-density IEEE 802.11ac/ax WLANs by means of simulations. We show that there may be critical interrelations among nodes in the spatial domain - even if they are located outside the carrier sense range of each other - in a chain reaction manner. Results also reveal that, while always selecting the widest available channel normally maximizes the individual long-term throughput, it often generates unfair situations where other WLANs starve. Moreover, we show that there are scenarios where DCB with stochastic channel width selection improves the latter approach both in terms of individual throughput and fairness. It follows that there is not a unique optimal DCB policy for every case. Instead, smarter bandwidth adaptation is required in the challenging scenarios of next-generation WLANs.