Joint Connection Level and Packet Level Analysis of Cognitive Radio Networks with VoIP Traffic

Castellanos-Lopez, S. Lirio; Cruz-Perez, F.A.; Rivero-Ángeles, Mario E.; Hernandez-Valdez, Genaro

doi:10.1109/jsac.2014.140319

Cited by 32 publications

(23 citation statements)

References 24 publications

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“…The performance of the studied flexible resource allocation (FRA) strategies is evaluated in terms of the maximum Erlang capacity of the CRN (defined as the maximum offered traffic load of secondary users for which QoS requirements are guaranteed in terms of blocking probability of new voice and data calls and forced termination probability of secondary voice calls) [35]. In order to calculate the Erlang capacity of the CR system, the maximum acceptable value of the new call blocking probability for voice and data secondary traffic and forced termination probability of voice secondary calls equals 2%.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The evaluated Erlang capacity of the cognitive radio system refers to the maximum offered traffic load of secondary users for which the QoS requirements are guaranteed. In our previous work [35], the Erlang capacity of a CRN was analyzed but only VoIP traffic was considered. In [35], neither different service types nor the individual and joint effect of each strategy on system performance was studied.…”

Section: Introductionmentioning

confidence: 99%

“…In our previous work [35], the Erlang capacity of a CRN was analyzed but only VoIP traffic was considered. In [35], neither different service types nor the individual and joint effect of each strategy on system performance was studied. In the present paper, service differentiation between real-time and elastic traffic is considered according to their different delay tolerance characteristics.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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“…Recently, implementation of cognitive radio cellular networks (CRCNs) has been investigated to solve both spectrum inefficiency and spectrum scarcity [4,5]. The main differences between traditional cellular networks and CRCNs lie in the so-called spectrum handoff, interruption due to the arrival of PUs (including the possibility of interruption of multiple sessions of SUs due to non-homogeneous bandwidth of PU and SU channels), and the fluctuating nature of spectrum resource because of the arrival and departure of PUs.…”

Section: Introductionmentioning

confidence: 99%

Modeling and performance analysis for mobile cognitive radio cellular networks

Corral-Ruiz

Cruz-Perez

Castellanos-Lopez³

et al. 2017

J Wireless Com Network

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In this paper, teletraffic performance and channel holding time characterization in mobile cognitive radio cellular networks (CRCNs) under fixed-rate traffic with hard-delay constraints are investigated. To this end, a mathematical model to capture the effect of interruption of ongoing calls of secondary users (SUs) due to the arrival of primary users (PUs) is proposed. The proposed model relies on the use of an independent potential interruption time associated with the instant of possible interruption for each ongoing call in every visited cell. Then, a Poisson process is used to approximate the secondary users' call interruption process due to the arrival of PUs. Based on this model and considering that unencumbered service time (UST) and cell dwell time (CDT) of SUs are independent generally distributed random variables, analytical formulae for both the probability distributions of channel holding times and inter-cell handoff attempts rate are derived. Also, a novel approximated closed-form mathematical expression for call forced termination probability of SUs is derived under the restriction that the UST is exponentially distributed. Additionally, by considering all the involved time variables exponentially distributed and employing fractional channel reservation to prioritize intra-and inter-cell handoff call attempts over new call requests, a queuing analysis to evaluate the call-level performance of CRCNs in terms of the maximum Erlang capacity is developed. The accuracy of our proposed mathematical models is extensively investigated under a variety of different evaluation scenarios for all the considered call-level performance metrics. Numerical results demonstrate that channel holding time statistics are highly sensitive to both interruption probability of ongoing secondary calls and type of probability distribution functions used to model CDT and UST. From the teletraffic perspective, numerical results reveal that the system Erlang capacity largely depends on the relative value of the mean secondary service time to the mean primary service time and the primary channels' utilization factor. Also, the obtained results show that there exists a critical utilization factor of the primary resources from which it is no longer possible to guarantee the required quality of service of SUs and, therefore, services with hard-delay constraints cannot be even supported in CRCNs.

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“…The analysis complexity of cognitive radio system was reduced effectively under the subjective effect and system analysis frame was constructed based on social dynamic influence. In [8], for VolP business, general Markov chain model was established and adjacent transition relations of states are solved. User connection properties and data packet loss performance were analyzed.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis in cognitive radio system under perfect spectrum sensing

Chen¹,

Gu²,

Zhang³

2015

Advances in Intelligent Systems Research

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Sensing period and optimization of user access in cognitive radio system are analyzed. By introducing birth and death process into cognitive radio system, a model of the queuing of primary users is built, based on which the probability of spectrum sensing and how the re-enter of the primary users effect on the spectrum usage of cognitive radio users are studied theoretically. Simulation results have justified the fitness of the model of joint analysis in the practical environment. Therefore we may conclude that it will achieve the highest overall spectrum efficiency by setting up configurations in a cognitive system according to the theory above.

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Joint Connection Level and Packet Level Analysis of Cognitive Radio Networks with VoIP Traffic

Cited by 32 publications

References 24 publications

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

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

Modeling and performance analysis for mobile cognitive radio cellular networks

Performance analysis in cognitive radio system under perfect spectrum sensing

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