Coalitional Game Theory based Cooperative Spectrum Sensing in CRNs

Gupta, Jyotirmay; Chauhan, Prakash; Nath, Madhabi; Manvithasree, Mekala; Deka, Sanjib Kumar; Sarma, Nityananda

doi:10.1145/3007748.3007759

Cited by 9 publications

(6 citation statements)

References 10 publications

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“…FC performs spectrum sensing using energy detection (ED) [22]. To synchronize SUs with PU, a time-slotted system is considered as in [23], [24] and SUs access the channel in a time division multiple access (TDMA) fashion. Each time slot (T ) is further divided into three sub-slots, named as prediction time (t p ), sensing time (t s ), and transmission time (t t ) respectively.…”

Section: System Model and Assumptionsmentioning

confidence: 99%

Cooperative Spectrum Prediction-Driven Sensing for Energy Constrained Cognitive Radio Networks

et al. 2021

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Spectrum prediction based sensing schemes minimize the overall energy consumption of the sensing module in cognitive radio networks (CRNs) by predicting the status of spectrum before performing actual physical sensing. But, the performance of independent or local prediction models suffer from inaccuracies. Cooperative mode of spectrum prediction is found to be suitable to overcome the issues of local prediction models. In this work, we propose a cooperative spectrum prediction-driven sensing scheme for energy constrained cognitive radio networks to reduce the energy consumption while maintaining the spectral efficiency. The proposed scheme first employs a long short term memory network technique to perform local spectrum prediction, which identifies the status of a channel before actual sensing to improve energy efficiency. Thereafter, a parallel fusion based cooperative spectrum prediction model is applied to minimize the errors induced in local prediction model. Finally, the resultant cooperative prediction model is combined with a spectrum sensing framework to perform sensing operation when the cooperative spectrum prediction results to an indeterminate state in order to enhance the spectral efficiency. Simulation results show the efficacy of the proposed scheme in terms of spectral efficiency and energy efficiency compared to similar schemes from literature.

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Section: System Model and Assumptionsmentioning

confidence: 99%

Cooperative Spectrum Prediction-Driven Sensing for Energy Constrained Cognitive Radio Networks

et al. 2021

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“…A distributed CSS is proposed coalitional game theoretic model for CRNs to improve the sensing performance in terms of detection probability [26]. In [27], the binary GA‐based soft fusion (SF) scheme for CSS in CRN is proposed to improve detection performance and bandwidth utilisation.…”

Section: Related Workmentioning

confidence: 99%

Distributed coalition formation game for enhancing cooperative spectrum sensing in cognitive radioad hocnetworks

Muthukkumar¹,

Duraisamy²

2020

IET Networks

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Cooperative spectrum sensing (CSS) among secondary users (SUs) in cognitive radio ad hoc networks exhibits an essential trade-off minimising the misdetection probability of the primary user and maintaining a reasonable false alarm probability to obtain efficient spectrum utilisation. In this study, distributed coalition formation game with a genetic algorithm is proposed to select the optimal coalitional head. It provides an incentive to SUs that improve their detection performance and cooperation among SUs. Since spectrum sensing will incur a cost for SUs, an incentive mechanism is necessary to motivate active participation. Consider the CSS problem as a non-transferable coalition game and it is used to allow the SUs to selforganise into disjoint coalitions while accounting for the CSS. The authors calculate payoff for each SU to form minimum winning coalition and to analyse their strategy profile for joining in coalition based on its utility maximisation. Simulation results reveal that the proposed algorithm has significantly improved sensing accuracy, minimised energy consumption and thereby enhanced CSS.

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“…The detection probability of SU i indicates their individual probability of detection and false alarm, i.e., P d,i and P f,i . Thus, Q i can be determined using (5).…”

Section: Proposed Schemementioning

confidence: 99%

“…In literature, several works have been presented [4][5][6][7][8], which addressed the issues of suitable SU selection for decision fusion to optimize the detection accuracy of CSS. The work discussed in [4] presents technique to select SUs based on their reliability for decision fusion where reliability of SUs were computed based on their detection results.…”

Section: Introductionmentioning

confidence: 99%

“…However, in this work, the types of fusion rule employed by FC was not discussed. A distributed technique for CSS was presented in [5], which uses the OR rule for fusion, and SUs were selected for fusion depending upon their reliability while how SUs' reliability were computed is not elaborated. A distancebased reliable CSS algorithm was put forwarded in the work [6] where reliability of SUs were decided based on SUs' distance from PU.…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Decision Fusion Scheme for Cooperative Spectrum Sensing for Cognitive Radio Networks

Chauhan

Deka

Sarma

2020

Applications of Internet of Things

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In this work, we propose an efficient decision fusion scheme for CSS, which achieves target cooperative probability of detection while maintaining a lower cooperative false alarm probability which eventually enhances the network throughput. The proposed scheme enables the fusion center (FC) to select secondary users (SUs) for decision fusion according to their reliability weights. For every SU, the reliability weight is computed by jointly considering the reporting information of SUs for past K time slots along with their detection and false alarm probabilities. The value of K is determined by computing the entropy on primary user (PU) activities observed on a designated channel over a certain period of time. Simulation-based study shows the efficacy of the proposed scheme in terms of reducing in cooperative probability of false alarm and improving the network throughput compared to conventional approach. Keywords Cooperative spectrum sensing • Reliability • Efficient decision fusion •

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Coalitional Game Theory based Cooperative Spectrum Sensing in CRNs

Cited by 9 publications

References 10 publications

Cooperative Spectrum Prediction-Driven Sensing for Energy Constrained Cognitive Radio Networks

Cooperative Spectrum Prediction-Driven Sensing for Energy Constrained Cognitive Radio Networks

Distributed coalition formation game for enhancing cooperative spectrum sensing in cognitive radioad hocnetworks

An Efficient Decision Fusion Scheme for Cooperative Spectrum Sensing for Cognitive Radio Networks

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