JENNA: a jamming evasive network-coding neighbor-discovery algorithm for cognitive radio networks [Dynamic Spectrum Management]

Cognitive radios operate in a particularly challenging wireless environment. Besides the strict requirements imposed by opportunistic coexistence with licensed users, cognitive radios may have to deal with other concurrent (either malicious or selfish) cognitive radios that aim at gaining access to the available spectrum resources with no regard to fairness or other behavioral etiquettes. By taking advantage of their highly flexible RF front-ends, they are able to mimic a licensed user´s behavior or simply 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 cognitive radio, 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 ensures 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.