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

More in details, the construction of a simulated observation database, to be used as a basis for selection, and the use of a diagnostic method to build a full covariance

For this part of the study, the 1D-Var has been run using the diagonal R matrix, the R matrix corresponding to the first iteration of the Desroziers’s diagnostic, and the R matrix

In this paper, our aim is to build the conflict graph that models the medium sharing due to the detection of the neighboring nodes’ activity. We assume that the RTS/CTS mechanism

We proposed a simple method to infer interference conflict graph in a Wi-Fi network.. The originality of our method is to propose an algorithm which relies only on AP local counters

Association Optimization in Wi-Fi Networks based on the Channel Busy Time Estimation.. Mohammed Amer, Anthony Busson,

To evaluate the accuracy of the proposed model, we explore several scenarios with different values of various network parameters, such as the IEEE 802.11 standard, the mean

In summary, at each packet transmission event, the PR unoccupancy per channel i, (P R (i) u ), is calculated by each CR node. The channel with the highest weight is then selected

Hence, by exploiting overhearing and PR occupancy properties, our strategy allows not only increasing the network reliability – since less PR-occupied channels will be selected –