Comments on "analysis of cognitive radio spectrum access with optimal channel reservation"

Martínez-Bauset, Jorge; Pla, Vicent; Pacheco-Paramo, Diego

doi:10.1109/lcomm.2009.090668

Cited by 19 publications

(14 citation statements)

References 1 publication

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“…In [13], [14] and [15], the case when a PU channel could be split into several SU channels are modeled through CTMCs. The authors of [13] and [14] mainly focus on the cases when there are infinite number of users, and both spectrum handover and non-handover cases are considered.…”

Section: Related Workmentioning

confidence: 99%

Modeling and Performance Analysis of Channel Assembling in Multichannel Cognitive Radio Networks With Spectrum Adaptation

Jiao

Pla

2012

IEEE Trans. Veh. Technol.

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Abstract-To accommodate spectrum access in multi-channel cognitive radio networks, channel assembling technique which combines several channels together as one channel has been proposed in many MAC protocols. However, analytical models for cognitive radio networks enabled with this technique have not been thoroughly investigated so far. In this paper, two representative channel assembling strategies are proposed considering spectrum adaptation and heterogeneous traffic, and the performance of these strategies is evaluated based on proposed continuous time Markov chain models. Moreover, approximations of these models in the quasi-stationary regime are analyzed and closedform capacity expressions are derived in different conditions. The performance of different strategies including the one without assembling is compared with each other based on the numerical results obtained from these models and validated by extensive simulations. Furthermore, simulation studies are also performed for other types of traffic distributions in order to evaluate the validity and the preciseness of the mathematical models. Through both analyses and simulations, we demonstrate that channel assembling represented by those investigated strategies can improve system performance if a proper strategy is selected with appropriate system parameter configurations.

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Section: Related Workmentioning

confidence: 99%

Modeling and Performance Analysis of Channel Assembling in Multichannel Cognitive Radio Networks With Spectrum Adaptation

Jiao

Pla

2012

IEEE Trans. Veh. Technol.

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“…However, handoff mechanisms fail when all the idle channels are occupied by PUs and SUs. Mathematically, it is represented by, j i N   (18) where N, i, j denote total number of channels, PU and SUtier1 in CRN respectively.…”

Section: Design Of Markov Model For 2-tier Crn With Spectrum Handoff mentioning

confidence: 99%

“…The expression for P D is derived from [18] and is expressed in (41) as per the designed Markov Model.…”

Section: {10}mentioning

confidence: 99%

Designing a Markov Model for the Analysis of 2-tier Cognitive Radio Network

Chakraborty¹,

Misra²

2013

IJACSA

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Abstract-Cognitive Radio Network (CRN) aims to reduce spectrum congestion by allowing secondary users to utilize idle spectrum bands in the absence of primary users. However, the overall user capacity and hence, the system throughput is bounded by the total number of available idle channels in the system. This paper aims to solve the problem of limited user capacity in basic CRN by proposing a 2-tier CRN that allows another tier (or layer) of secondary users to transmit, in addition to the already existing set of primary and secondary users in the system. Markov Models are designed step-wise to map the interaction between primary and secondary users in both tiers by including suitable traffic distribution models and system parameters. Spectrum handoff is also incorporated in the developed Markov Models. Performance analysis is carried out in terms of SU transmission, dropping, blocking and handoff probabilities along with mathematical formulation of the overall SU throughput in 2-tier CRN. It confirms better spectrum utilization in spectrum handoff enabled 2-tier CRN over basic CRN with enhancement in quality of service for secondary users in terms of reduced dropping and blocking probabilities.

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“…The first phase is MAC protocol design itself, which aims at proposing feasible schemes to make CRNs access spectrum more efficiently [2][3][4]. The second phase is to build analytical models in order to help us better understand the dynamics behind these schemes and evaluate the performance of different strategies [5][6][7][8][9]. In this study, we mainly focus on the second phase and analyze the performance of channel aggregation represented by two new strategies, i.e., the Greedy strategy and the Dynamic strategy, when spectrum adaptation is enabled.…”

Section: Introductionmentioning

confidence: 99%

“…This work is motivated by the observation that the performance of SU networks with various channel aggregation strategies is not thoroughly analyzed through mathematical models. For example, in [5][6][7], the performance of an SU network when a channel for Primary Users (PUs) can be divided into several channels for SUs is analyzed based on a Continuous Time Markov Chain (CTMC) model. In [8,9], the performance of several channel aggregation strategies when spectrum adaptation is not enabled is studied through CTMC models.…”

Section: Introductionmentioning

confidence: 99%

Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

Jiao

Pla

2011

NETWORKING 2011 Workshops

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Abstract. In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models.

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Comments on "analysis of cognitive radio spectrum access with optimal channel reservation"

Cited by 19 publications

References 1 publication

Modeling and Performance Analysis of Channel Assembling in Multichannel Cognitive Radio Networks With Spectrum Adaptation

Modeling and Performance Analysis of Channel Assembling in Multichannel Cognitive Radio Networks With Spectrum Adaptation

Designing a Markov Model for the Analysis of 2-tier Cognitive Radio Network

Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

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