Capacity Limits for a Cognitive Radio Network under Fading Channel

In this paper, performance evaluation of a cognitive radio network is conducted. The analysis is based on stochastic network calculus. The system is supposed to work in a Time Division Multiple Access (TDMA) mode with fixed slot length. The wireless channel is modeled as a Gilbert-Elliott (GE) fading channel, where the channel quality transits between state ON and state OFF according to a Markov chain. Spectrum sensing errors, which can be classified into mis-detection and false-alarm, are taken into consideration. Particularly, a stochastic arrival curve for spectrum sensing error process, and a stochastic service curve for GE channel, are derived. In addition, performance distribution bounds are obtained based on stochastic network calculus. Furthermore, numerical calculations are made to show the capacity limits under delay constraints.