Spectrum Assignment in Cognitive Radio Networks for Internet-of-Things Delay-Sensitive Applications Under Jamming Attacks

Abstract

The expected widespread usage of Internet-of-Things (IoT) devices and the associated diversity of applications will place extra pressure on network resources including bandwidth availability. In networking within IoT, spectrum scarcity requires the consideration of the adaptive cognitive radio (CR) technology to achieve interference-free and on-demand IoT solutions for a number of applications. However, CR networks share the same security weaknesses of legacy wireless networks. Jamming is considered a common attack, where jammers can attack networks in a proactive or reactive approach. In this paper, we study the channel assignment problem under both proactive and reactive jamming attacks. Specifically, we propose a novel probabilistic-based channel assignment mechanism that aims at minimizing the invalidity ratio of CR packet transmissions subject to delay constraints. The proposed scheme exploits the statistical information of licensed primary users activities, fading conditions and jamming attacks over idle channels to provide communicating CR IoT devices with the most secured channels of lowest invalidity ratios. Simulation results show that our proposed security, availability, and quality-aware channel assignment algorithm can significantly improve network performance.