Queueing Analysis for Cognitive Radio Networks With Lower-Layer Considerations
In this paper, the queue dynamics of Secondary Users (SUs) in a multi-SU and multi-channel cognitive radio network is analyzed to obtain the expressions of Quality of Service (QoS) metrics. Specially, in the analysis, the authors take several lower-layer mechanisms and settings into account, including Automatic Repeat reQuest (ARQ), finite-size buffer, Adaptive Modulation and Coding (AMC) and non-ignorable spectrum sensing errors. By modeling the queue dynamics as a Markov chain, they derive the analytical expressions of queue length, packet dropping rate and packet collision rate. Based on these expressions, the QoS metrics including delay, packet loss rate and throughput are calculated further.