Spectrum Assignment in Cognitive Radio Networks: A Comprehensive Survey

Τράγος, Ηλίας; Zeadally, Sherali; Fragkiadakis, Alexandros; Siris, Vasilios A.

doi:10.1109/surv.2012.121112.00047

Cited by 342 publications

(207 citation statements)

References 126 publications

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“…This way, colors act as frequencies and hetero-chromatic edges guarantee element pairs with different frequencies. Although widely used, Tragos et al [10] conclude that the model is not accurate enough, because it does not reflect all the information. For instance, the authors suggest that the information regarding adjacent channel interferences should be incorporated into the graph.…”

Section: Modelling Based On a Multilayer Graphmentioning

confidence: 99%

Nonlinear Negotiation Approaches for Complex-Network Optimization: A Study Inspired by Wi-Fi Channel Assignment

Marsa-Maestre

Hoz

Giménez-Guzmán

et al. 2017

Conflict Resolution in Decision Making

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Abstract. In this paper, we study a problem family inspired by a prominent network optimization problem (graph coloring), enriched and extended towards a real-world application (Wi-Fi channel assignment). We propose a utility model based on this scenario, and we generate an extensive set of test cases, against which we run both a complete information optimizer and two nonlinear negotiation approaches -a hill-climber and an approach based on simulated annealing (SA). We show that, for the larger-scale scenarios, the SA negotiation approach significantly outperforms the optimizer while running in roughly one tenth of the computation time. Also, we point out interesting patterns regarding the relative performance of the two approaches depending on the properties of the underlying graphs.

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Section: Modelling Based On a Multilayer Graphmentioning

confidence: 99%

Nonlinear Negotiation Approaches for Complex-Network Optimization: A Study Inspired by Wi-Fi Channel Assignment

Marsa-Maestre

Hoz

Giménez-Guzmán

et al. 2017

Conflict Resolution in Decision Making

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“…In CRSN, the SUs (second users, SU) can use the spectrum of PUs (Primary users, PU) only in the case of don't have interfere with PUs. Once the PU appears, SU must vacate the occupied frequency band, search and switch to another idle channel, this process is called spectrum handoff [4]. There are three basic spectrum handoff models [5,6]: stay and wait, predetermined target channel list, sensing idle spectrums instantly.…”

Section: Introductionmentioning

confidence: 99%

“…It thus leads to the parameters have some uncertainty. Existing decision methods including fuzzy method [4,8], the simple weighted algorithm [9], the dynamic weight decision method [10], analytic hierarchy process, the technique for order preference by similarity to ideal solution [11] etc. However, the above methods require more parameters and the computation is relatively complexity.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Handoff Method Based on Extenics for Cognitive Radio Sensor Networks

Wang

Wan²,

Ouyang³

et al. 2016

Int. J. Onl. Eng.

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Abstract-A spectrum handoff model and optimal channel decision method based on Extenics have been proposed in order to resolve the optimal channel decision problem of spectrum handoff in Cognitive Radio Sensor Networks. The method of matter-element Extenics is used to analyses the spectrum handoff process. The channel state through the spectrum sensing and status information of the primary users is analyzed and transformed by matter-element Extenics. Then the parameters to determine the best channel are calculated on the basis of Extenics correlation function. Finally the optimal channel is selected. The simulation results show that the proposed method can improve spectrum utilization efficiency of Cognitive Radio Sensor Networks and can reduce the interrupt probability of second users.

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“…The channel availability is importance in CR because a high number of idle channel offers flexibility for channel switching and minimizes re-clustering due to changes in channel states [7]. The channel availability parameter has not only been applied in the clustering algorithm but also in solving the channel sensing order [8][9] and spectrum assignment [10].…”

mentioning

confidence: 99%

“…As a consequence, the fuzzy algorithm is capable of handling uncertainties of real time application more accurate than the probabilistic model [10].…”

mentioning

confidence: 99%