A CR Spectrum Allocation Algorithm in Smart Grid Wireless Sensor Network

He, Wei; Li, Ké; Zhou, Qiang; Li, Songnong

doi:10.3390/a7040510

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…To prevent spectrum holes assigning channels in static manner efficiently utilize allocated spectrum is explained in [16,17]. To improve the capacity of system Wei et al [18] have proposed a non-cooperative CA strategy based on game theory in SG scenario. In [19] a Dynamic Spectrum Allocation (DSA) scheme based on fairness using Binary Particle Swarm Optimization ((BPSO)) has been proposed for SGCN.…”

Section: Introductionmentioning

confidence: 99%

Clustering-based Energy-Efficient Resource Allocation in Cognitive Radio Based Smart Grid

Anbuselvi¹,

Ananthi²,

Aruna³

2023

Preprint

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Cognitive Radio (CR) has been recognized as one of the intellectual solutions for Smart Grid environment to transmit high volume data over various environments and distribute the electricity to the customers. The inspiration of this work is to reduce the interference and allocate channels efficiently that improves the and utilization fairness of the Smart Grid (SG) network through a clustering-based EnergyEfficient Power Allocation algorithm among Secondary Users. Mathematical equations have been developed for the performance parameters such as channel reward, user reward, Jain’s fairness index, throughput and power calculation which has been simulated using MATLAB R2020b.

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Section: Introductionmentioning

confidence: 99%

Clustering-based Energy-Efficient Resource Allocation in Cognitive Radio Based Smart Grid

Anbuselvi¹,

Ananthi²,

Aruna³

2023

Preprint

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“…CRs use the existing spectrum through opportunistic access to the licensed bands without interfering with the licensed users. CRs determine the spectrum portions unoccupied by the licensed users known as spectrum holes or white spaces, and allocate the best available channels for CR communication [19], [20].After identification of available spectrum holes, the spectrum utilization can be improved through joint spatial and temporal spectrum sharing. SG applications, especially demand response management, can benefit from joint spatial and temporal spectrum sharing [21].…”

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confidence: 99%

mentioning

confidence: 99%

Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols

Khan

Rehmani

Reisslein

2016

IEEE Commun. Surv. Tutorials

314

145

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Traditional power grids are currently being transformed into Smart Grids (SGs). SGs feature multi-way communication among energy generation, transmission, distribution, and usage facilities. The reliable, efficient, and intelligent management of complex power systems requires integration of highspeed, reliable, and secure data information and communication technology into the SGs to monitor and regulate power generation and usage. Despite several challenges, such as trade-offs between wireless coverage and capacity as well as limited spectral resources in SGs, wireless communication is a promising SG communications technology. Cognitive Radio Networks (CRNs) in particular are highly promising for providing timely SG wireless communications by utilizing all available spectrum resources. We provide in this paper a comprehensive survey on the CRN communication paradigm in SGs, including the system architecture, communication network compositions, applications, and CR-based communication technologies. We highlight potential applications of CR-based SG systems. We survey CR-based spectrum sensing approaches with their major classifications. We also provide a survey on CR-based routing and MAC protocols, and describe interference mitigation schemes. We furthermore present open issues and research challenges faced by CR-based SG networks along with future directions.Index Terms-Advanced metering infrastructure (AMI), Communication architecture, Cognitive radio network (CRN), Smart grid (SG).1553-877X (c) 2 to license holders on a long-term basis for large geographical regions. This fixed spectrum allocation can result in inefficient spectrum utilization. Cognitive radios (CRs) operating on the principle of Dynamic Spectrum Access (DSA) may be a suitable option to solve these spectrum inefficiency problems [18]. CRs use the existing spectrum through opportunistic access to the licensed bands without interfering with the licensed users. CRs determine the spectrum portions unoccupied by the licensed users known as spectrum holes or white spaces, and allocate the best available channels for CR communication [19], [20].After identification of available spectrum holes, the spectrum utilization can be improved through joint spatial and temporal spectrum sharing. SG applications, especially demand response management, can benefit from joint spatial and temporal spectrum sharing [21]. Machine-to-machine (M2M) communication is an emerging paradigm for providing ubiquitous connectivity between devices to communicate autonomously without human intervention. However, a high number of connected devices can heavily congest the spectrum in existing communication networks. CR technology may be a suitable option for mitigating the potential spectrum shortage arising from M2M communications in the SG [22]. B. Contribution of this Survey ArticleWhile a few overview articles have outline some selected aspects of CR communication in the SG [23]- [25], to the best of our knowledge, there is no prior survey that comprehensively covers CR-based...

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“…In general, cognitive radio networks, primary users (PUs) and secondary users (SUs) seek to maximize their profits in the competition and cooperation, which means that the game theory has become an effective method to study the relationship between PUs and SUs [7]. The spectrum sharing model based on the Cournot game is originally proposed by previous studies [8,9].…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Dynamic Spectrum Allocation Algorithm Based on Cournot Game in Maritime Cognitive Radio Communication System

Zhang

2017

Algorithms

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Abstract:The recent development of maritime transport has resulted in the demand for a wider communication bandwidth being more intense. Cognitive radios can dynamically manage resources in a spectrum. Thus, building a new type of maritime cognitive radio communication system (MCRCS) is an effective solution. In this paper, the enhanced dynamic spectrum allocation algorithm (EDSAA) is proposed, which is based on the Cournot game model. In EDSAA, the decision-making center (DC) sets the weights according to the detection capability of the secondary user (SU), before adding these weighting coefficients in the price function. Furthermore, the willingness of the SU will reduce after meeting their basic communication needs when it continues to increase the leasable spectrum by adding the elastic model in the SU's revenue function. On this basis, the profit function is established. The simulation results show that the EDSAA has Nash equilibrium and conforms to the actual situation. It shows that the results of spectrum allocation are fair, efficient and reasonable.

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A CR Spectrum Allocation Algorithm in Smart Grid Wireless Sensor Network

Cited by 7 publications

References 8 publications

Clustering-based Energy-Efficient Resource Allocation in Cognitive Radio Based Smart Grid

Clustering-based Energy-Efficient Resource Allocation in Cognitive Radio Based Smart Grid

Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols

An Enhanced Dynamic Spectrum Allocation Algorithm Based on Cournot Game in Maritime Cognitive Radio Communication System

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