An agent-based simulation framework for cognitive radio studies

Dzikowski, Jacek; Hood, Cynthia S.

doi:10.4108/icst.simutools2009.5654

Cited by 7 publications

(2 citation statements)

References 21 publications

(14 reference statements)

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“…Simulations have been conducted for evaluating the performance scope of Fuzzy Guided Integrative Factors (FGIF)-based spectrum sensing. The evaluation metrics such as spectrum access realization (Jabbari et al , 2010), energy conversation (Akyildiz et al , 2006) and interference by PUs (Dzikowski and Hood, 2015) have been considered to estimate the significance of the proposed model. The minimal interference, maximum spectrum access realization and less energy conversation signify fair allocation of spectrum bands under integrative factors of service quality to SUs in spectrum sensing.…”

Section: Experimental Studymentioning

confidence: 99%

Fuzzy guided integrative factors-based spectrum decision-making in cognitive radio networks

S²,

Ramesh

2020

IJIUS

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PurposeElectronic devices aid communication during new communication phases and the scope of cognitive radio networks has changed communication paradigms through efficient use of spectrums. The communication prototype of cognitive radio networks defines user roles as primary user and secondary user in the context of the spectrum allocation and use. The users who have licensed authority of the spectrum are denoted as primary users, while other eligible users who access the corresponding spectrum are secondary users.Design/methodology/approachThe multiple factors of transmission service quality can have a negative influence due to improper scheduling of spectrum bands between primary users and secondary users. There are considerable contributions in contemporary literature concerning spectrum band scheduling under spectrum sensing. However, the majority of the scheduling models are intended to manage a limited number of transmission service quality factors. Moreover, these service quality factors are functional and derived algorithmically from the current corresponding spectrum. However, there is evidence of credible performance deficiency regarding contemporary spectrum sensing methodsFindingsThis article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.Originality/valueThis article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.

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Section: Experimental Studymentioning

confidence: 99%

Fuzzy guided integrative factors-based spectrum decision-making in cognitive radio networks

S²,

Ramesh

2020

IJIUS

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“…Most traditional network simulators are non-agent-based simulators. Existing non-agent-based simulation packages fall into two categories: general network simulators with additional wireless networking components such as NS-2, OMNET++, and wireless network specified simulators such as J-Sim [27]. This subsection will introduce some of them and illustrate how each of them being used in different CRN research works.…”

Section: Non-agent-based Network Simulatormentioning

confidence: 99%

A Survey on Simulation Tools and Testbeds for Cognitive Radio Networks Study

Dong,

Chen,

et al. 2018

Preprint

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Efficient utility of radio spectrum has been a hot topic as the wireless communication spectrum is a precious resource. The past decade has witnessed intensive research in spectrum sharing techniques. Most of the techniques are based on cognitive radio networks (CRNs) because cognitive capabilities are essential for optimizing spectrum efficiency and guaranteeing safe coexistence in the presence of the spectrum uncertainty. However, due to the high complexity of the problem, most research has been limited to theoretical analysis. It is nontrivial to build a simulator that is capable of carrying out a comprehensive experimental study. In this paper, a survey is conducted to provide a big picture of the available simulators in CRNs research. By illustrating their major functionalities, the insight enables researchers to select tools that match their needs. In addition, with a better understanding of the advantages and constraints, this survey aims at providing a guideline for simulator designers who have been trying to meet the requirements from the CRN research community.

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2013

Radio Resource Allocation and Dynamic Spectrum Access

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An agent-based simulation framework for cognitive radio studies

Cited by 7 publications

References 21 publications

Fuzzy guided integrative factors-based spectrum decision-making in cognitive radio networks

Fuzzy guided integrative factors-based spectrum decision-making in cognitive radio networks

A Survey on Simulation Tools and Testbeds for Cognitive Radio Networks Study

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