Sensing nodes selection and data fusion in cooperative spectrum sensing

Zhou, Yiming; Zhou, Zheng; Li, Bin

doi:10.1049/iet-com.2013.1036

Cited by 6 publications

(9 citation statements)

References 26 publications

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“…From (13) and (14) in Lemma 1, it can be seen that P (F C) f and P (F C) m monotonically increase and decrease, respectively, over N . Thus, from (19), (20), (21) and (22), the increased number of SUs helps both CSS schemes improve the MDP, however, causing a higher FAP.…”

Section: B Cooperative Spectrum Sensing (Css)mentioning

confidence: 93%

“…The overhead energy caused by the CSS was also dealt with in [12] where an energy-efficient node selection was proposed to select the best node based on the binary knapsack problem. In [13], the selection of sensing nodes can also be realised by linearly weighting the sensing data at all sensing nodes. Considering the scenario when only partial information of SUs and PUs is available in the wireless sensor networks, an energy-efficient sensor selection algorithm has been proposed in [14] to minimise the energy consumption while still satisfying the average detection probability.…”

Section: Introductionmentioning

confidence: 99%

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Cooperative spectrum sensing with secondary user selection for cognitive radio networks over Nakagami‐ m fading channels

2016

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This paper investigates cooperative spectrum sensing (CSS) in cognitive wireless radio networks (CWRNs). A practical system is considered where all channels experience Nakagami-m fading and suffer from background noise. The realisation of the CSS can follow two approaches where the final spectrum decision is based on either only the global decision at fusion centre (FC) or both decisions from the FC and secondary user (SU). By deriving closed-form expressions and bounds of missed detection probability (MDP) and false alarm probability (FAP), we are able to not only demonstrate the impacts of the m-parameter on the sensing performance but also evaluate and compare the effectiveness of the two CSS schemes with respect to various fading parameters and the number of SUs. It is interestingly noticed that a smaller number of SUs could be selected to achieve the lower bound of the MDP rather using all the available SUs while still maintaining a low FAP. As a second contribution, we propose a secondary user selection algorithm for the CSS to find the optimised number of SUs for lower complexity and reduced power consumption. Finally, numerical results are provided to demonstrate the findings.

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Section: B Cooperative Spectrum Sensing (Css)mentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Cooperative spectrum sensing with secondary user selection for cognitive radio networks over Nakagami‐ m fading channels

2016

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“…As defined in (13) and (14), the attenuation coefficient is proportional to b i,j , and the distance is inversely proportional to b i,j . When (11) and (12) are determined, the auto-logistic model of the Markov random field is degraded into the Ising model owing to the first-order neighborhood system, which is similar to the image segmentation. Thus, the conditional probability can be expressed as…”

Section: Modeling Processmentioning

confidence: 99%

Broadband Spectrum Sensing of Distributed Modulated Wideband Converter Based on Markov Random Field

Li¹,

Zhu²,

Zhou³

et al. 2018

ETRI Journal

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The Distributed Modulated Wideband Converter (DMWC) is a networking system developed from the Modulated Wideband Converter, which converts all sampling channels into sensing nodes with number variables to implement signal undersampling. When the number of sparse subbands changes, the number of nodes can be adjusted flexibly to improve the reconstruction rate. Owing to the different attenuations of distributed nodes in different locations, it is worthwhile to find out how to select the optimal sensing node as the sampling channel. This paper proposes the spectrum sensing of DMWC based on a Markov random field (MRF) to select the ideal node, which is compared to the image edge segmentation. The attenuation of the candidate nodes is estimated based on the attenuation of the neighboring nodes that have participated in the DMWC system. Theoretical analysis and numerical simulations show that neighboring attenuation plays an important role in determining the node selection, and selecting the node using MRF can avoid serious transmission attenuation. Furthermore, DMWC can greatly improve recovery performance by using a Markov random field compared with random selection.

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“…In a case, whereby a single SU sensing is shadowed, in severe multipath fading and shadowing effects, the SU may not reliably detect the primary user (PU) signal and access the channel when there is a primary signal present causing interference to the licensed PU . To overcome the hidden terminal problem and increase the spectrum sensing reliability, cooperative spectrum sensing (CSS) has been studied in References . In general, CSS can be classified as either being centralized or distributed.…”

Section: Introductionmentioning

confidence: 99%

“…Centralized CSS operates in two categories as follows: (i) the observations are preprocessed by the SUs to produce their measurement or test statistics. From the reported measurement, the fusion center FC makes the final judgment; (ii) the FC processes the total received samples forwarded from each SU to make the final decision . Category (ii) requires a large portion of overhead as SUs report their collected samples.…”

Section: Introductionmentioning

confidence: 99%

Efficient evidence‐based decision fusion scheme for cooperative spectrum sensing in cognitive radio networks

Simpson

Sun

2020

Trans Emerging Tel Tech

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In this article, an evidence based decision fusion cooperative spectrum sensing (CSS) schemes has been considered for overcoming the hidden terminal problem, improving reliability, and increasing SU agility. Under practical conditions, the combination of conflicting evidences with the classical Dempster-Shafer theory (DS theory) rule may produce counter-intuitive results when combining the secondary users (SUs) sensing data evidence leading to poor CSS performance. In order to overcome and minimize the effect of conflicting data, and to enhance performance of the CSS system, a novel efficient evidence-based decision fusion scheme CSS is proposed. The approach is based on the credibility of evidence from the SUs sensing decision, which represents the similarity or the relation among the different SUs sensing data evidence, and a dissociability degree measure that indicates the quality or clarity of the SUs sensing data evidence. Furthermore, a weighted averaging factor determined by the credibility and dissociability of the SU sensing data evidence is proposed. Simulation results presented show that under practical conditions the proposed scheme enhances the performance of the CSS system when compared to traditional fusion rules that do not take into account the difference in local sensing reliability between the SUs.

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Sensing nodes selection and data fusion in cooperative spectrum sensing

Cited by 6 publications

References 26 publications

Cooperative spectrum sensing with secondary user selection for cognitive radio networks over Nakagami‐ m fading channels

Cooperative spectrum sensing with secondary user selection for cognitive radio networks over Nakagami‐ m fading channels

Broadband Spectrum Sensing of Distributed Modulated Wideband Converter Based on Markov Random Field

Efficient evidence‐based decision fusion scheme for cooperative spectrum sensing in cognitive radio networks

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