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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/11179
Title: Channel allocation and ultra-reliable communication in CRNs with heterogeneous traffic and retrials: A dependability theory-based analysis
Authors: Kulshrestha, Rakhee
Keywords: Mathematics
Cognitive radio networks
Markov chain
Channel failure
Retrial queue
Heterogeneous traffic
Channel reservation
Issue Date: May-2020
Publisher: Elsevier
Abstract: The current research efforts on Fifth Generation (5G) of wireless communication systems have identified the need for large extent improvements in accessibility and reliability of communication services. In this respect, Cognitive Radio (CR) has been envisioned as a key 5G enabler that allows dynamic spectrum access without causing interference to licensed (primary) users and can tackle the challenge of ultra reliable communication. Channel failures, which are generally caused due to hardware and software failure and/or due to intrinsic features such as fading and shadowing, can easily result in network performance degradation. In cognitive radio networks (CRNs), the connections of unlicensed (secondary) users are inherently vulnerable to breaks due to channel failures as well as licensed users’ arrivals. To explore the advantages of channel reservation and retrial phenomenon on performance improvement in error-prone channels, we propose and analyze dynamic spectrum access (DSA) scheme by also taking balking and reneging behavior into account. Moreover, since 5G networks should comprise heterogeneous applications that may have different Quality of Service (QoS), thus the present study facilitates the arrival of heterogeneous secondary users with access privilege variations. In addition, most previous works have studied the stationary performance of CRNs, however, those may not be adequate in practice, notably when the time horizon of operations is finite. This paper investigates the transient dynamics from the perspectives of dependability theory in CRNs. Furthermore, the whole system is modeled using a multi-dimensional continuous time Markov chain (CTMC) and numerical results illustrate the potential of the proposed scheme to achieve major gains in the performance of error-prone CRNs.
URI: https://www.sciencedirect.com/science/article/pii/S0140366419315531
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11179
Appears in Collections:Department of Mathematics

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