Energy harvesting cognitive radio networks with strategic users: A two-class queueing model with retrials

Sun, Ke; Liu, Yunan; Li, Kaili

doi:10.1016/j.comcom.2022.12.017

Cited by 8 publications

(4 citation statements)

References 29 publications

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“…The queuing theory is a useful analytical tool that can be utilized in the process of designing and optimizing admission-control systems in cognitive radio networks (CRNs) [13]. In the context of CRNs, where dynamic spectrum access and effective resource usage are of the utmost importance, queuing theory makes it possible to conduct a systematic examination of the queuing dynamics, service rates, and user arrivals in the network [14]. It is possible to conduct an analysis of the performance indicators that are essential for admission control by modeling the network as a queuing system [15].…”

Section: Proposed Frameworkmentioning

confidence: 99%

Optimizing Priority Queuing Systems with Server Reservation and Temporal Blocking for Cognitive Radio Networks

Behera,

Imoize,

Singh

et al. 2024

Telecom

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In the domain of cognitive radio (CR), unlicensed users have the opportunity to efficiently use available spectrum bands without interfering with licensed primary users (PUs). Our study addresses the challenge of secondary user (SU) spectrum shortage due to high arrival rates of licensed users. We propose two models aimed at improving the average total waiting time for SUs in such scenarios. These models incorporate non-acquired and preemptive priority mechanisms within the M/D/1 model of a PU delay system. Through quantitative evaluations and Monte Carlo simulations, we evaluate the performance of these models. Our findings show significant improvements in average waiting time for both PUs and SUs, especially under the priority scheme. Furthermore, we explore these models in the context of real-time systems, considering the limited buffer capacity for both user types. This further improves the average waiting time for PUs and SUs in both priority schemes. Our contribution lies in providing effective solutions to mitigate SU shortages in CR networks, providing insight into priority-based approaches and real-time system considerations.

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Section: Proposed Frameworkmentioning

confidence: 99%

Optimizing Priority Queuing Systems with Server Reservation and Temporal Blocking for Cognitive Radio Networks

Behera,

Imoize,

Singh

et al. 2024

Telecom

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“…The primary focus was on analyzing and modeling the energy efficiency of these networks, with the specific goal of achieving environmentally friendly and sustainable wireless communications. In the paper 28 , an energy-harvesting CRN was examined using a queueing model. The analysis involved investigating equilibrium strategies for users aiming to maximize their utility, employing a game-theoretical approach, and determining the conditions for a unique Nash equilibrium.…”

Section: Literature Reviewmentioning

confidence: 99%

A Stochastic Framework for Energy Saving in Cognitive Radio Networks using N-Policy Multiple Sleep Mode

Srivastava,

Sharma

2023

Preprint

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Cognitive Radio Networks (CRNs) represent a cutting-edge solution to the growing problem of limited available spectrum. With the increasing demand for wireless communication services, the efficient utilization of spectrum resources becomes paramount. Green CRNs offer a dynamic and opportunistic approach by intelligently sensing and accessing idle licensed spectrum, known as white spaces focusing on environmentally conscious communication methods. These unoccupied frequency bands, left unused by primary users (PUs), present an opportunity for CRNs to enhance spectrum utilization and alleviate the spectrum scarcity challenge. In the presented study, we concentrate on energy conservation in “Green” CRNs, with a specific focus on base stations (BSs). We suggest an energy-efficient approach that utilizes multiple sleep modes employing an N-policy, with the objective of addressing the growing need for environmentally friendly communication practices. To model the energy-saving process and assess system performance, we employ a semi-Markov process (SMP). Moreover, the paper provides a detailed analysis of performance metrics, encompassing average latency for Secondary Users (SUs), throughput of the system, energy saving factor, and energy consumption.

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Ding Xu . [11], [12], [23], [25], [29], [30], [31], [32], [34], [40], [42], [44], [45], [47]. There are many different possible variants of information transmission in CRN s which require consideration of different queueing systems as their descriptors, see, e.g., [36].…”

Section: Introductionmentioning

confidence: 99%

Admission Control in Priority Queueing System With Servers Reservation and Temporal Blocking Admission of Low Priority Users

et al. 2023

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We analyse a cell of Cognitive Radio Network (CRN ) as the multiline queueing system supplying service to two Markovian arrival flows of users. Primary (or licensed) users called as High Priority Users (HPU s) have a preemptive priority over the secondary (cognitive) users called as Low Priority Users (LPU s). The HPU s are dropped upon the arrival only if all servers are occupied by HPU s. If at the arrival epoch all servers are busy but some of them provide service to LPU s, service of one LPU is immediately interrupted and service of the HPU begins in the released server. A LPU is accepted only if the number of busy servers at arrival epoch is less than the defined in advance threshold M . Otherwise, the LPU is permanently lost or becomes a retrial user. A retrial user repeats attempts to receive service later after random time intervals. The LPU whose service is interrupted is either lost or transferred to a virtual place called as orbit. The users placed in the orbit may be impatient and can renege the system. The service time follows an exponential probability distribution with the rate determined by the user's type. After loss of a HPU , admission of LPU s is blocked. LPU s are informed that their access is temporarily suspended and do not generate new requests until blocking expires. The purpose of the research is the optimization of threshold M and admission blocking period duration. Behavior of the system is described by a multidimensional continuous-time Markov chain. Its generator, ergodicity condition and invariant distribution are derived. Expressions for performance indicators are given. Numerical results demonstrating usefulness of blocking and significance of account of correlation in arrivals are presented. E.g., in the presented example of cost criterion optimization blocking gives 18 percent profit comparing to the system without blocking.

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Energy harvesting cognitive radio networks with strategic users: A two-class queueing model with retrials

Cited by 8 publications

References 29 publications

Optimizing Priority Queuing Systems with Server Reservation and Temporal Blocking for Cognitive Radio Networks

Optimizing Priority Queuing Systems with Server Reservation and Temporal Blocking for Cognitive Radio Networks

A Stochastic Framework for Energy Saving in Cognitive Radio Networks using N-Policy Multiple Sleep Mode

Admission Control in Priority Queueing System With Servers Reservation and Temporal Blocking Admission of Low Priority Users

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