Inference of a clear channel assessment based conflict graph

Abstract

We consider an IEEE 802.11 network composed of several Access Points (APs) managed by one controller. The controller relies on pieces of information describing the network state as channels, load, associated stations, conflicts, etc. to configure and optimize the network. In this paper, we propose a method that infers the way the different channels are shared between APs according to the Clear Channel Assessment (CCA) mechanism. It is represented through a conflict graph where an edge exists if two APs are able to detect each other. As this detection is sometimes partial, the links are weighted. Our method relies on measures already available on most of Wi‐Fi products and does not generate any traffic except the transmission of these measures to the controller. A Markov network and an optimization problem are then proposed to infer the weights of the conflict graph. Our solution is shown accurate on a large set of simulations performed with the network simulator ns‐3.

Mitigating starvation in dense WLANs: A multi-armed Bandit solution

“…For the second starting point, its location is based on the conflict graph between APs. Note that two APs are said to be in conflict when they cannot transmit at the same time (see [29]). Then, we simply decrease the TX PWR of APs in a round-robin fashion until the conflict graph of APs reaches an average degree of 0.5.…”

Use of a Weighted Conflict Graph in the Channel Selection Operation for Wi-Fi Networks

“…The coefficients of the matrix S are substituted by the coefficients w j,i (0 ≤ w j,i ≤ 1) that represent the partial CCA detection between APs. In [7], we describe a method to infer the weighted conflict graph of an infrastructure-based Wi-Fi network. The coefficient w j,i depends on the AP location, the radio environment and the channel allocation as two APs using two orthogonal channels do not interfere with each other.…”

Ad‐hoc, mobile, and wireless networks

“…Centralized approaches rely on a central controller that thanks to its global view of the network can allocate resources according to network status, traffic patterns and priorities, etc. For instance, a controller could improve channel utilization in IEEE802.11 networks where Access Points (APs) usually simply relay on Clear Channel Assessment (CCA) to detect concurrent transmissions 13 . Clustering‐based approaches by grouping (mobile) nodes into groups (i.e., clusters) aims to optimize network performances 14 .…”

“…The fifth paper “Inference of a clear channel assessment based conflict graph” 13 tackles the interference issue in IEEE802.11 networks. The authors proposes a passive method to infer a weighted conflict graph that represents both full and partial CCA detection among APs.…”