Auction based game theory in cognitive radio networks for dynamic spectrum allocation

Sofia, D. Sumithra; Edward, A. Shirly

doi:10.1016/j.compeleceng.2020.106734

Cited by 22 publications

(12 citation statements)

References 15 publications

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“…We remark that for the smallest number of SUs, the performance of [19] is better than ours; but for the higher number, our results exceed those of [19]. This phenomenon can be explained by the increase in overall profit, when the number of cooperated SUs increases, and will be the same for the PU.…”

Section: B Pu's Performancecontrasting

confidence: 67%

“…But neither cooperation nor competition is extremely positive or negative: each has its advantages and its limits [11]- [17]. Auction mechanism approach helps the SUs to get a part of the unused license band, for a lease, from the PUs [19,20]. The authors of [19] proposed a new framwork, based on the negligible mutual interferences and satisfaction levels among the SUs, to share the leased band.…”

Section: Related Workmentioning

confidence: 99%

“…Auction mechanism approach helps the SUs to get a part of the unused license band, for a lease, from the PUs [19,20]. The authors of [19] proposed a new framwork, based on the negligible mutual interferences and satisfaction levels among the SUs, to share the leased band. Their simulation results showed that the proposed mechanism enhanced the spectral efficiency of the SUs and increased the PUs' revenues.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, their withdrawal gives more profit to other players. C. Comparison between our performances and those of [19] In order to compare our performances in the cooperative form with those of [19] based on table 1.1 and table 1.2 of the mentioned paper, we take the same number of SUs and the same cost = 30. After the evaluation of the spectral efficiency, and the PU's profit , we obtain tables IV and V, respectively.…”

Section: B Pu's Performancementioning

confidence: 99%

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Monopoly-Market-based Cooperation in Cognitive Radio Networks

Lakhal

Guennoun

2020

JCOMSS

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In a cognitive radio network (CRN), the primary users (PUs) do not operate their spectra, full time. Thus, they can sell them to the secondary users (SUs), for a second use, during the free time slots. In this article, we assume that the market is perfect, monopolized by a single PU, and all players are rational. After formulating the PU's profit, we established a necessary and sufficient condition that guarantees the introduction of the PU into the market. In addition, the expressions of the SUs' profits, showed us that in non-cooperative form, some ones got zero profit, even after maximizing their profits. Therefore, we have considered to study the effect of cooperation on the profits of this category of SUs. By following this step, we established a cooperation strategy, to avoid zero profits for all SUs. In order to analyze the impact of this cooperation on the PU, we have expressed the profits of the PU in the cooperative and non-cooperative forms; as result, we found that the cooperation between SUs brought better than the non-cooperative form.

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Section: B Pu's Performancecontrasting

confidence: 67%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: B Pu's Performancementioning

confidence: 99%

See 2 more Smart Citations

Monopoly-Market-based Cooperation in Cognitive Radio Networks

Lakhal

Guennoun

2020

JCOMSS

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“…An auction methodology reported in Sumithra Sofia and Shirly Edward 19 considers interference constraints for enhanced spectrum utilization. The presented game theory‐based auction model selects the winner considering the satisfaction level and interference constraints to overcome the limitations in traditional auction mechanisms like a second‐price auction and Vickrey–Clarke–Groves auction models.…”

Section: Related Workmentioning

confidence: 99%

Optimized channel prediction and auction‐based channel allocation for personal cognitive networks

Jeyakanth¹,

Venkatakrishnan²,

Chitra³

2022

Int J Communication

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Cognitive networks are stands out as intelligent technology which evolved to enhance spectrum utilization. Secondary users are allowed to utilize the primary user's frequency bands on idling times. Identifying the idle licensed spectrum is achieved through spectrum sensing. The spectrum holes should be explored such that a suitable spectrum can be selected and allocated to the secondary users. Existing spectrum sensing and selection schemes have limitations due to interferences. Thus, an optimization algorithm based on bioinspired improved weed optimization was presented in this research work for enhanced channel utilization. The optimization model explores the channel characteristics and reduces the primary network interferences through its optimal solution. Further, Markov greedy-based auction scheme was presented for channel allocation. Considering the channel capacity, delay, and switching rates the allocation is performed to enhance the overall system performance. Simulation analysis demonstrates the superior performance of the proposed model over existing techniques like particle swarm optimization and genetic algorithm.

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A study on the channel bonding in IoT networks: Requirements, applications, and challenges

Kandar

Chyne

Sur

et al. 2023

Int J Communication

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The most well-known sort of remote Internet connection is wireless local area networks (WLANs) due to its unsophisticated operation and deployment. Subsequently, the quantity of gadgets getting to the Internet through WLANs, for example, PCs, cell phones, or wearables, is expanding radically at the equivalent time that applications' throughput necessities do. To provide wireless networks with supplementary spectral resources, the researchers are considering the aggregation of frequency spectrums in licensed, unlicensed, and shared access (SA) bands. Channel aggregation/channel bonding (CA/CB) techniques accumulate quite a few channels together as one channel for the purpose of achieving better bandwidth utilization. In this study, we focus on reliable CA/CB techniques in different wireless networks. CA/CB procedures are utilized for empowering higher information rates by transmitting in more extensive channels, accordingly expanding range proficiency with the assured secure channel for communication. We also discuss the spectral scarcity issues in today's wireless IoT network. This paper presents an extensive survey on CA/CB procedures and methods, issues and challenges, and open research areas related to IoT devices. We analyze the performance of channel CA/CB strategies in the different wireless networks too.

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Auction based game theory in cognitive radio networks for dynamic spectrum allocation

Cited by 22 publications

References 15 publications

Monopoly-Market-based Cooperation in Cognitive Radio Networks

Monopoly-Market-based Cooperation in Cognitive Radio Networks

Optimized channel prediction and auction‐based channel allocation for personal cognitive networks

A study on the channel bonding in IoT networks: Requirements, applications, and challenges

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