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RESEARCH PRODUCT

Channel Occupancy-Based Dynamic Spectrum Leasing in Multichannel CRNs: Strategies and Performance Evaluation

Amogh RajannaIndika A. M. BalapuwadugeMostafa KavehFrank Y. Li

subject

business.industryComputer scienceQuality of serviceComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSComputerApplications_COMPUTERSINOTHERSYSTEMS020206 networking & telecommunications020302 automobile design & engineering02 engineering and technologyBlocking (statistics)Cognitive radioDigital subscriber line0203 mechanical engineeringDynamic pricing0202 electrical engineering electronic engineering information engineeringResource allocationNetwork performanceElectrical and Electronic EngineeringbusinessSimulationComputer network

description

Spectrum leasing has been proposed as an effective approach for enabling more flexible spectrum utilization in CRNs. In CRNs, a primary network (PN) which consists of multiple primary users (PUs) can lease part of the licensed spectrum to secondary users (SUs) in exchange for operational benefits. The focus of this study is to investigate how and to what extent the PN allows spectrum leasing in CRNs, considering the QoS requirements of the PN and the secondary network (SN). Correspondingly, we propose two dynamic spectrum leasing strategies, which can improve the QoS performance of SUs while ensuring sufficient remuneration for PUs. In order to dynamically adjust the portion of leased bandwidth, two forms of leasing algorithms, which are based on channel occupancy of the PN and the SN respectively are proposed. Analytical models are developed to characterize system centric performance metrics including capacity, blocking probability, and forced termination probability in both networks. Furthermore, a dynamic pricing scheme for spectrum leasing and utility-based resource allocation is introduced. Finally the performance of dynamic leasing is compared quantitatively with that of static leasing and approaches without leasing. Numerical results obtained from both analysis and simulations show that dynamically adjusted spectrum leasing improves network performance.

https://doi.org/10.1109/tcomm.2016.2521723