Alfa, Attahiru SulePla, V.Martinez-Bauset, J.Casares-Giner, V.2016-08-052016-04Alfa, AS, Pla, V, Martinez-Bauset, J & Casares-Giner, V 2016, 'Discrete time analysis of cognitive radio networks with imperfect sensing and saturated source of secondary users', Computer Communications, vol. 79, pp. 53-65.0140-366410.1016/j.comcom.2015.11.012http://hdl.handle.net/2263/56204Sensing is one of the most challenging issues in cognitive radio networks. Selection of sensing parameters raises several tradeoffs between spectral efficiency, energy efficiency and interference caused to primary users (PUs). In this paper we provide representative mathematical models that can be used to analyze sensing strategies under a wide range of conditions. The activity of PUs in a licensed channel is modeled as a sequence of busy and idle periods, which are represented as alternating Markov phase renewal processes. The representation of the secondary users (SUs) behavior is also largely general: the duration of transmissions, sensing periods and the intervals between consecutive sensing periods are modeled by phase type distributions, which constitute a very versatile class of distributions. Expressions for several key performance measures in cognitive radio networks are obtained from the analysis of the model. Most notably, we derive the distribution of the length of an effective white space; the distributions of the waiting times until the SU transmits a given amount of data, through several transmission epochs or uninterruptedly; and the goodput when an interrupted SU transmission has to be restarted from the beginning due to the presence of a PU.en© 2015 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Computer Communications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Communications, vol. 79, pp. 53-65, 2016. doi : 10.1016/j.comcom.2015.11.012.Cognitive radio (CR)SensingPerformance modelingDiscrete time Markov modelPhase type distributionPrimary users (PUs)Postprint Article