Robust Detection of Incumbents in Cognitive Radio Networks Using Groups

Abstract

Cognitive radio is a wireless technology aimed at improving the efficiency use of the radio-electric spectrum, thus facilitating a reduction in the load on the free frequency bands. Cognitive radio networks can scan the spectrum and adapt their parameters to operate in the unoccupied bands. To avoid interfering with licensed users operating on a given channel, the networks need to be highly sensitive, which is achieved by using cooperative sensing methods. Current cooperative sensing methods are not robust enough against occasional or continuous attacks. This article outlines a Group Fusion method that takes into account the behavior of users over the short and long term. On fusing the data, the method is based on giving more weight to user groups that are more unanimous in their decisions. Simulations have been performed in a dynamic environment with interferences. Results prove that when attackers are present (both reiterative or sporadic), the proposed Group Fusion method has superior sensing capability than other methods.