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Sensing is a fundamental aspect in cognitive radio networks and one of the most complex issues. In the design of sensing strategies, a number of tradeoffs arise between throughput, interference to primary users, and energy consumption. This paper provides several Markovian models that enable the analysis and evaluation of sensing strategies under a broad range of conditions. The occupation of a channel by primary users is modeled as alternating idle and busy intervals, which are represented by a Markov phase renewal process. The behavior of secondary users is represented mainly through the duration of transmissions, sensing periods, and idle intervals between consecutive sensing periods. These durations are modeled by phase-type distributions, which endow the model with a high degree of generality. Unlike our previous work, here the source of secondary users is nonsaturated, which is a more practical assumption. The arrival of secondary users is modeled by the versatile Markovian arrival process, and models for both finite and infinite queues are built. Furthermore, the proposed models also incorporate a quite general representation of the resumption policy of an SU transmission after being interrupted by PUs activity. A comprehensive analysis of the proposed models is carried out to derive several key performance indicators in cognitive radio networks. Finally, some numerical results are presented to show that, despite the generality and versatility of the proposed models, their numerical evaluation is perfectly feasible.

Discrete-Time Analysis of Cognitive Radio Networks with Nonsaturated Source of Secondary Users