JENNA: A Jamming Evasive Network-Coding Neighbor-Discovery Algorithm for Cognitive Radio Networks

In this paper we address the problem of neighbor discovery in cognitive radio networks. Cognitive radios operate in a particularly challenging wireless environment. In such an environment, besides the strict requirements imposed by the opportunistic co-existence with licensed users, cognitive radios may have to deal with other concurrent (either malicious or selfish) cognitive radios which aim at gaining access to most of the available spectrum resources with no regards to fairness or other behavioral etiquettes. By taking advantage of their highly flexible radio devices, they are able to mimic licensed users behavior or simply to jam a given channel with high power. This way these concurrent users (jammers) are capable of interrupting or delaying the neighbor discovery process initiated by a normal cognitive radio network which is interested in using a portion of the available spectrum for its own data communications. To solve this problem we propose a Jamming Evasive Network-coding Neighbor-discovery Algorithm (JENNA) which assures complete neighbor discovery for a cognitive radio network in a distributed and asynchronous way. We compare the proposed algorithm with baseline schemes that represent existing solutions, and validate its feasibility in a single hop cognitive radio network.