Performance Evaluation of Joint Admission and Eviction Controls of Secondary Users in Cognitive Radio Networks

Hasan, Ahmadi; AlQahtani, Salman A.

doi:10.1007/s13369-015-1692-z

Cited by 3 publications

(5 citation statements)

References 13 publications

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“…Cognitive radio (CR) has emerged as a promising technology to realize dynamic spectrum access and increase the efficiency of a largely under utilized spectrum. As it was defined in [1,2], the cognitive radio network (CRN) is a network made up of CRs by extending the radio link features to network layer function and above. By means of CRs cooperation, the network is able to sens its environment, learn from the history, and accordingly decide the best spectrum settings.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of finite-source cognitive networks with non-reliable services using simulation

Nemouchi¹,

Sztrik²

2018

Proceedings of the 10th International Conference on Applied Informatics

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As the evolution of wireless communication technology, the available spectrum resources become scarce. The cognitive radio (CR) is a dynamic spectrum access technique which provides the capability to share a wireless channel between licensed and unlicensed users opportunistically (also called Primary Users-PU and Secondary Users-SU). In this paper stochastic simulation is used for performance evaluation of cognitive radio network. A finite-source retrial queuing model with two service units is proposed. A priority queue and an orbit are assigned to the PUs and SUs respectively. The proposed queueing system contains two interconnected, not independent subsystems. The Primary Channel Service (PCS) and the Secondary Channel Service (SCS) are not reliable and the services are assumed to be subject to a random failure with probability p1 and p2 for the PCS and SCS, respectively. The failure of the service may block the servers and the request retransmission process starts immediately. The novelty of this work is to analyze the effect of the failure probability on the mean and the variance of the response time of the PUs and SUs, and on the Utilization of the PCS and SCS. The inter-event times are supposed to be exponentially, hypo-exponentially, hyper-exponentially and lognormally distributed random variables, depending on different cases during simulation. By the help of simulation we compare the effect of the non-reliability of the servers in different combination of distributions on the first and second moments of the response times of the requests, and the utilization of the system by illustrating on different figures.

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Section: Introductionmentioning

confidence: 99%

Performance evaluation of finite-source cognitive networks with non-reliable services using simulation

Nemouchi¹,

Sztrik²

2018

Proceedings of the 10th International Conference on Applied Informatics

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“…As it was defined in [1,2], the cognitive radio network (CRN) is a network made up of CRs by extending the radio link features to network layer function and above. By means of CRs cooperation, the network is able to sense its environment, learn from the history, and accordingly decide the best spectrum settings.…”

Section: Introductionmentioning

confidence: 99%

Performance Simulation of Non-reliable Servers in Finite-Source Cognitive Radio Networks with Collision

Nemouchi

Sztrik

2017

Information Technologies and Mathematical Modelling. Queueing Theory and Applications

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Abstract. This paper introduces a finite-source retrial queueing system which models cognitive radio networks. We assume two non-independent frequency bands servicing two classes of users: Primary Users (PUs) and Secondary Users (SUs). A service unit with a priority queue and another service unit with an orbit are assigned to the PUs and SUs, respectively.In this work, we focus on the non-reliability of the servers and the collisions at the secondary servers. The primary and secondary servers are subject to random breakdowns and repairs. A collision is introduced at the retrial part of the cognitive radio network. This conflict invokes the interruption of a servicing packet when a new arriving call requests the server unit.The novelty of the investigation is the non-reliability of servers and the inclusion of conflicts at the secondary server.By the use of simulation, we analyze the effect of the non-reliability of the servers on the mean response time of the secondary users.

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“…Call buffering strategy that can be used to reduce the forced termination probability of preempted secondary calls. That is, if spectrum handoff is not possible (i.e., no white spaces are available), preempted secondary sessions may be queued into a buffer to wait for a spectrum hole [25,28]. In this case, when a queued SU finds a new spectrum hole, it is allowed to continue transmitting its information.…”

Section: Introductionmentioning

confidence: 99%

“…Surprisingly, transmission delay has not been previously considered as performance metric [10][11][12][13][14][15][16][17][18][19][20][21][22][23]28]. Moreover, previous studies that address CRNs with heterogeneous traffic and spectrum adaptation [10][11][12][13][14][15][16][17][18][19][20][21][22][23] have not considered the use of call buffering, which is a relevant mechanism to exploit the elasticity of best effort traffic in benefit of both real-time and elastic secondary sessions.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, previous studies that address CRNs with heterogeneous traffic and spectrum adaptation [10][11][12][13][14][15][16][17][18][19][20][21][22][23] have not considered the use of call buffering, which is a relevant mechanism to exploit the elasticity of best effort traffic in benefit of both real-time and elastic secondary sessions. Exception of this are [28,33,34]; however, in these works, neither Erlang capacity nor transmission delay is considered.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and performance evaluation of resource management mechanisms in heterogeneous traffic cognitive radio networks

Castellanos-Lopez¹,

Cruz-Perez

Hernandez-Valdez³

et al. 2017

J Wireless Com Network

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In this paper, the Erlang capacity achieved by the separate or joint use of several resource management mechanisms commonly considered in the literature (spectrum aggregation, spectrum adaptation, call buffering, channel reservation, selective interruption, and preemptive prioritization) to mitigate the effects of secondary call interruptions in cognitive radio networks (CRNs) is evaluated and compared. Heterogeneous traffic is considered, and service differentiation between real-time and elastic (data) traffic is done in terms of their different delay tolerance characteristics. The aim of our investigation is to identify the most relevant resource management mechanisms to improve the performance of the considered networks. As such, both the individual and joint effect of each resource management mechanisms on system performance are evaluated with the objective of comparing the gains in capacity achieved by each resource management mechanism studied in this work. For this purpose, the different resource management mechanisms studied are carefully combined and, for each resulting strategy, optimization of its configuration is presented to maximize the achievable Erlang capacity. For the performance evaluation of the considered strategies in heterogeneous traffic CRNs, a general teletraffic analysis is developed. Numerical results show that spectrum adaptation and call buffering are the mechanisms that best exploit the elasticity of delay-tolerant traffic in heterogeneous traffic CRNs and, therefore, most significantly improve system performance.

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Performance Evaluation of Joint Admission and Eviction Controls of Secondary Users in Cognitive Radio Networks

Cited by 3 publications

References 13 publications

Performance evaluation of finite-source cognitive networks with non-reliable services using simulation

Performance evaluation of finite-source cognitive networks with non-reliable services using simulation

Performance Simulation of Non-reliable Servers in Finite-Source Cognitive Radio Networks with Collision

Analysis and performance evaluation of resource management mechanisms in heterogeneous traffic cognitive radio networks

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