Evaluation of Theoretical Interference Estimation Metrics for Dense Wi-Fi Networks
Srikant Manas Kala, Vanlin Sathya, Winston K.G. Seah, Hirozumi Yamaguchi, Teruo Higashino · 2021
To meet the rising data offloading demands, IEEE 802.11-based WiFi networks have undergone gradual and consistent densification through Overlapping Basic Service Set (OBSS) deployments. With the upcoming 802.11ax standard, dense and ultra-dense deployments (DNs/UDNs) will become the norm, and the detrimental impact of endemic interference on network capacity will further exacerbate. In traditional Wireless Mesh Networks (WMNs), Theoretical Interference Estimation Metrics (TIEMs) are widely used as an indirect measure of interference. TIEMs are instrumental to channel allocation (CA) and performance prediction, routing, and scheduling algorithms. However, the exact nature of the relationship between TIEMs and performance parameters such as network capacity has not been investigated. TIEMs will likely serve similar roles in sixth-generation 802.11ax WiFi networks, and a TIEM-Capacity analysis will improve their application. In this work, we study the TIEM-capacity relationship through nonparametric regression. This study investigates the impact of WMN topology on their relationship by considering four carefully designed Wireless Mesh Network (WMN) topologies in the experiments. We consider four popular Theoretical TIEMs and a broad set of 100 channel assignment (CA) schemes. The investigations are carried out on IEEE 802.1lg/n WMNs simulated in ns-3. We then analyze the TIEM-capacity feature relationship parameters to classify the TIEMs in terms of their reliability and the ability to model interference. Finally, we validate the outcome of our study on a dense 802.11ac experimental testbed. The TIEM identified as the most suitable for dense scenarios by the proposed analytical framework demonstrates over 95% accuracy and a correlation of 0.98 with dense network capacity.