Spectrum Allocation Based on Game Theory in Cognitive Radio Networks

Ni, Qiufen; Zhu, R. Y.; Wu, Zhenguo; Sun, Yanjing; Zhou, Lingyun; Zhou, Bin

doi:10.4304/jnw.8.3.712-722

Cited by 21 publications

(10 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ni et al [14] used game theory for efficient and flexible spectrum assignment in cognitive radio networks. They have classified allocation problems into co-operative and non-cooperative models.…”

Section: Literature Surveymentioning

confidence: 99%

Spectrum Allocation in Cognitive Radio: A PSO-based Approach

Mishra

Sagnika

Singh

et al. 2019

Period. Polytech. Elec. Eng. Comp. Sci.

View full text Add to dashboard Cite

Cognitive radio systems have taken a fore-running position in the wireless communication technology. With most of the communication taking place through multi-carrier systems, the allocation of available spectrum to various carriers is a prominent issue. Since cognitive systems provide an environment of dynamic spectrum allocation, it becomes necessary to perform dynamic spectrum allocation swiftly with due consideration of parameters, like power consumption, fair distribution and minimal error. This paper considers a Particle Swarm Optimization-based approach, popularly used for solving large problems involving complex solution spaces to reach an optimal solution within feasible time. The mentioned spectrum allocation problem has been solved using PSO with a view to maximize the total transfer rate of the system, within specified constraints of maximum error rate, maximum power consumption and minimum transfer rate per user. The results have been compared with the existing Genetic Algorithm-based approach and have proved to be more effective.

show abstract

Section: Literature Surveymentioning

confidence: 99%

Spectrum Allocation in Cognitive Radio: A PSO-based Approach

Mishra

Sagnika

Singh

et al. 2019

Period. Polytech. Elec. Eng. Comp. Sci.

View full text Add to dashboard Cite

show abstract

“…Generally speaking, game theory has been applied for the optimization of various back-end functions of ICT networks such as resource allocation and routing optimizations [11][12][13] but also for optimizing power usage [14] as well as for spectrum sharing [15].…”

Section: Game Theoretical Applied To Ict Networkmentioning

confidence: 99%

Modeling the relationship between network operators and venue owners in public Wi-Fi deployment using non-cooperative game theory

Spruytte

Benhamiche

Chardy

et al. 2019

J Wireless Com Network

View full text Add to dashboard Cite

Wireless data demands keep rising at a fast rate. In 2016, Cisco measured a global mobile data traffic volume of 7.2 Exabytes per month and projected a growth to 49 Exabytes per month in 2021. Wi-Fi plays an important role in this as well. Up to 60% of the total mobile traffic was off-loaded via Wi-Fi (and femtocells) in 2016. This is further expected to increase to 63% in 2021. In this publication, we look into the roll-out of public Wi-Fi networks, public meaning in a public or semi-public place (pubs, restaurants, sport stadiums, etc.). More concretely we look into the collaboration between two parties, a technical party and a venue owner, for the roll-out of a new Wi-Fi network. The technical party is interested in reducing load on its mobile network and generating additional direct revenues, while the venue owner wants to improve the attractiveness of the venue and consequentially generate additional indirect revenues. Three Wi-Fi pricing models are considered: entirely free, slow access with ads or fast access via paid access (freemium), and paid access only (premium). The technical party prefers a premium model with high direct revenues, the venue owner a free/freemium model which is attractive to its customers, meaning both parties have conflicting interests. This conflict has been modeled using non-cooperative game theory incorporating detailed cost and revenue models for all three Wi-Fi pricing models. The initial outcome of the game is a premium Wi-Fi network, which is not the optimal solution from an outsider's perspective as a freemium network yields highest total payoffs. By introducing an additional compensation scheme which corresponds with negotiation in real life, the outcome of the game is steered toward a freemium solution.

show abstract

“…Under the optimal condition that the total MSE is the minimum, according to the measuring value of each sensor the optimal weight value can be found in a self-adaptive way. The aggregated value of X can get the optimum [18]. The total MSE is: Base on the relative theories for extreme value of multivariate function, we can obtain corresponding weighted factor when the total MSE has minimum value:…”

Section: Amentioning

confidence: 99%

A Data-aggregation Scheme for WSN based on Optimal Weight Allocation

Zou¹,

Liu²

2014

JNW

View full text Add to dashboard Cite

Since the measuring accuracy and environment of each sensor are different, there must exist difference in the correctness of measurement. If the testing data is not processed and utilized with distinction, it will cause impreciseness to the testing results and lead to errors of the system. It is necessary to selectively distinguish the importance among the sensors, contraposing the situation of each sensor in the testing system and the accuracy of tests. So the related concepts of data aggregation technology in wireless sensor networks and the aggregation algorithm performance evaluation criteria are introduced. The core problem in WSN, aggregation operation for sensing data, is studied deeply. The problems in node data group when the distributed clustering technology is implemented to WSN are also analyzed. Then a distributed K-mean clustering algorithm based on WSN is proposed. On the basis of this improved algorithm, we realize a network data aggregation processing mechanism based on adaptive weighted allocation of WSN. DKC algorithm is mainly used to process the testing data of bottom nodes. When reducing the data redundancy it can provide more accurate field testing information and system status information. It can make rapid packet for the network nodes. The packed data will be used to provide correct judgement, according to the size of its corresponding weight, to acquire more reasonable results. The experiments have demonstrated that our method can greatly decrease the data redundancy of WSN and save large amount of storage resources. The network bandwidth consumption is also reduced. So this scheme has high efficiency and good scalability.

show abstract

Spectrum Allocation Based on Game Theory in Cognitive Radio Networks

Cited by 21 publications

References 38 publications

Spectrum Allocation in Cognitive Radio: A PSO-based Approach

Spectrum Allocation in Cognitive Radio: A PSO-based Approach

Modeling the relationship between network operators and venue owners in public Wi-Fi deployment using non-cooperative game theory

A Data-aggregation Scheme for WSN based on Optimal Weight Allocation

Contact Info

Product

Resources

About