Performance analysis of a cognitive radio network with imperfect spectrum sensing

In Cognitive Radio Networks (CRNs), spectrum sensing is performed by secondary (unlicensed) users to utilize transmission opportunities, so-called white spaces or spectrum holes, in the primary (licensed) frequency bands. Secondary users (SUs) perform sensing upon arrival to find an idle channel for transmission as well as during transmission to avoid interfering with primary users (PUs). In practice, spectrum sensing is not perfect and sensing errors including false alarms and misdetections are inevitable. In this paper, we develop a continuous-time Markov chain model to study the effect of false alarms and misdetections of SUs on several performance measures including the collision rate between PUs and SUs, the throughput of SUs and the SU delay in a CRN. Numerical results indicate that sensing errors can have a high impact on the performance measures

Analysis of asynchronous cognitive radio system with imperfect sensing and bursty primary user traffic

Due to copyright restrictions, the access to the full text of this article is only available via subscription.This paper presents a theoretical analysis of the spectrum utilization levels in a cognitive radio system. We assume that the traffic of the primary network is bursty and asynchronous with the secondary network, which performs imperfect spectrum sensing. Collisions of the primary and the secondary packets are assumed to result in increased packet error probabilities. We present primary and secondary utilization levels under optimized secondary transmission periods for varying primary traffic characteristics and secondary sensing performance levels. The results are also validated by extensive Monte Carlo simulations. We find that an asynchronous cognitive radio network with imperfect spectrum sensing is feasible when optimized transmission periods are used. The effects of primary traffic’s burst pattern and secondary sensing performance are discussed.European Commission ; TÜBİTA