Overlap Regions and Grey Model-Based Approach for Interference Avoidance in Cognitive Radio Networks

Quach Minh Thao (1) , Dramane Ouattara (1) , Francine Krief (1) , Hicham Khalifé (2) , Mohamed Aymen Chalouf (3)

1 LaBRI - Laboratoire Bordelais de Recherche en Informatique
2 THALES COMMUNICATIONS & SECURITY
3 IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires

Ensuring high quality of communication while reducing interference remains a challenge in unplanned wireless mobile networks. The Cognitive Radio Ad Hoc Networks (CRAHNs) with cooperative sensing promise to be an appropriate solution for achieving high data rates. In this article, we evaluate the impact of cognitive radio transmissions on primary radio communications by characterizing precisely based on the position of the primary and secondary radio emitters, the vulnerable areas where interference causes impact to primary radios. Furthermore, we show that either reducing the overlap area or avoid the high density primary receivers area could considerably reduce the impact on the primary system while the secondary transmission is operating. Through OMNeT++ simulations, we illustrate that there is a dependency between the size of the overlap area: the smaller the overlap region, the smaller the impact on the receivers in this area. However, we also show that the distribution of the PR receivers are also a vital perspective on preventing interference. We hence investigate a solution to predict primary radio receivers position using the Grey Prediction Model.

Domaines: Informatique et théorie des jeux [cs.GT]; Réseaux et télécommunications [cs.NI]

Quach Minh Thao, Dramane Ouattara, Francine Krief, Hicham Khalifé, Mohamed Aymen Chalouf. Overlap Regions and Grey Model-Based Approach for Interference Avoidance in Cognitive Radio Networks. International Conference on Ubiquitous and Future Networks, IEEE ICUFN, 2013. ⟨hal-00853905⟩