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RESEARCH PRODUCT

System Times and Channel Availability for Secondary Transmissions in CRNs: A Dependability Theory based Analysis

Vicent PlaFrank Y. LiIndika A. M. Balapuwaduge

subject

Reliability theoryComputer Networks and CommunicationsComputer scienceAerospace Engineering02 engineering and technologyCommunications system0203 mechanical engineering0202 electrical engineering electronic engineering information engineeringDependabilityCognitive radio networks (CRNs)Resource managementElectrical and Electronic EngineeringSpectrum accessMarkov chainCumulative distribution functionGuaranteed availability020206 networking & telecommunications020302 automobile design & engineeringINGENIERIA TELEMATICAUniformization (probability theory)System timesReliability engineeringCognitive radioChannel availabilityAutomotive EngineeringContinuous-time Markov chains (CTMCs)UnavailabilityCommunication channel

description

[EN] Reliability is of fundamental importance for the performance of secondary networks in cognitive radio networks (CRNs). To date, most studies have focused on predicting reliability parameters based on prior statistics of traffic patterns from user behavior. In this paper, we define a few reliability metrics for channel access in multichannel CRNs that are analogous to the concepts of reliability and availability in classical dependability theory. Continuous-time Markov chains are employed to model channel available and unavailable time intervals based on channel occupancy status. The impact on user access opportunities based on channel availability is investigated by analyzing the steady-state channel availability and several system times such as mean channel available time and mean time to first channel unavailability. Moreover, the complementary cumulative distribution function for channel availability is derived by applying the uniformization method, and it is evaluated as a measure of guaranteed availability for channel access by secondary users. The precision and the correctness of the derived analytical models are validated through discrete-event-based simulations. We believe that the reliability metric definitions and the analytical models proposed in this paper have their significance for reliability and availability analysis in CRNs.

10.1109/tvt.2016.2585200http://hdl.handle.net/10251/99503