Transient analysis of energy-saving strategy for cognitive radio networks using G-queue with heterogeneity

dc.contributor.authorKulshrestha, Rakhee
dc.date.accessioned2025-09-22T04:44:22Z
dc.date.available2025-09-22T04:44:22Z
dc.date.issued2024-02
dc.description.abstractEnergy efficiency, high data speeds, and effective spectrum utilization stand as the primary factors governing 5G and beyond networks. A base station (BS) in a cognitive radio network (CRN) that conserves energy during sleep periods is a promising contender for achieving more effective spectrum allocation. An efficient energy-saving strategy is offered in this study to achieve greener communication in wireless cellular networks. This study aims to propose and analyze an energy-saving scheme for the BS, taking into account the heterogeneity and reliability of networks. The entire system is modeled as a three-dimensional Markov chain by establishing a discrete-time preemptive priority queueing model with single vacation, heterogeneous packets, and negative packets such as viruses. Then, the transient analysis of the Markov chain is performed using the recursive method. Utilizing the transient probability distribution, we present numerical results derived from reliability analysis and queueing analysis to substantiate the validity of the proposed model. Furthermore, results based on the energy-saving degree are showcased to affirm the effectiveness of the proposed scheme. Finally, a reward cost function is obtained depending on the successful transmission of secondary packets, and the Quasi-Newton method is used to determine the optimal reward cost.en_US
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0140366424000070
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/19490
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectMathematicsen_US
dc.subjectCognitive radio networken_US
dc.subjectEnergy-saving strategyen_US
dc.subjectG-queueen_US
dc.subjectHeterogeneous packetsen_US
dc.titleTransient analysis of energy-saving strategy for cognitive radio networks using G-queue with heterogeneityen_US
dc.typeAnimationen_US

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