Auction Based Spectrum Trading for Cognitive Radio Networks

Tehrani, Mohsen Nader; Uysal, Murat

doi:10.1109/lcomm.2013.043013.130371

Cited by 25 publications

(16 citation statements)

References 10 publications

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“…In this way, the seller maximizes its profit and the auction ends. On this matter, an auction‐based spectrum trading approach is applied to maximize both the total buyer's satisfaction and the seller's profit . Specifically, the shared used model and the risk of imperfect spectrum sensing are considered in order to derive an expression that optimizes the sensing time (ie, the time that the base station needs in order to identify spectrum opportunities, thus avoiding to make interferences with other base stations).…”

Section: Related Workmentioning

confidence: 99%

Matching theory as enabler of efficient spectrum management in 5G networks

Tsirakis

López-Aguilera

Agapiou

et al. 2019

Trans Emerging Tel Tech

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This paper analyzes the spectrum trading problem in virtualized fifth generation networks to enhance the network performance with respect to the spectrum utilization. The problem is modeled as a many‐to‐many matching game with utility‐based preferences and determines the matching between mobile network operators and mobile virtual network operators. The two proposed versions of utility functions for each set aim at maximizing the satisfaction of both sets with conflicting interests and improving the overall spectrum efficiency. In the simulation evaluation, the proposed scheme is compared with three different schemes in terms of the system utility, individual, and pair matching satisfaction. We also investigate the scalability aspects, the strategy plan impact on the matching performance of our proposed scheme, and at the same time, we attempt to make appropriate assumptions closer to reality. Our proposed scheme shows much better performance than the other schemes achieving a quite high level of satisfaction for the matching result on both sets.

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Section: Related Workmentioning

confidence: 99%

Matching theory as enabler of efficient spectrum management in 5G networks

Tsirakis

López-Aguilera

Agapiou

et al. 2019

Trans Emerging Tel Tech

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“…In this circumstance, how to establish a suitable and flexible contact to balance secondary user's interest and stabilize the market need to be further considered [24], [25]. Furthermore, most of the existing works are based on a basic assumption: The information interactions between the primary users and secondary users as well as the secondary users themselves are transparent and smooth, and the time, cost and transmit power involved in the course can be ignored [26], [27]. Thus, a specific and feasible interaction protocol used in the auction behavior should be investigated and formed.…”

Section: Introductionmentioning

confidence: 99%

Preference-Based Spectrum Pricing in Dynamic Spectrum Access Networks

Sheng

Hua

et al. 2018

IEEE Trans. Serv. Comput.

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(2016) Preference-based spectrum pricing in dynamic spectrum access networks. IEEE Transactions on Services Computing (99). ISSN 1939ISSN -1374 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/61903/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. Abstract-With market-driven secondary spectrum trading, licensed users can receive benefits in terms of monetary rewards or various transmission services, thus setting a fair pricing structure by suitably defining spectrum quality characteristics and accurately addressing participant's requirement is a key issue. In this paper, we investigate the pricing-based spectrum access by casting the problem of spectrum pricing into a Hotelling game model according to spectrum quality diversity. Particularly, we first build a pricing system model where unused spectrum from primary systems with different qualities forms a spectrum pool and can be divided into a number of uniform channels. A secondary user purchases a channel for usage according to its selection preference which is closely related to the channel quality and spectrum evaluation. The secondary user not only needs to consider the channel's quality and price, but also the interference cost on primary system. Detailed analysis on the policy preference of both primary system and secondary buyer are provided. By forming a game problem of spectrum pricing between primary and secondary users, we apply the Hotelling game model to handle the interaction between the participants. Specifically, by fixing Nash equilibrium of the game, an iterative algorithm for spectrum pricing is proposed based on the distribution characteristics of secondary user's preference. Essential analysis for the existence and uniqueness of the Nash equilibrium along with algorithm's convergence conditions are provided. Numerical results are also supplemented to show the effectiveness of the proposed algorithm in ensuring spectrum owner's profit.

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“…In [24], the authors investigated a short term secondary spectrum trading between one PU and multiple SUs in a hybrid spectrum market to optimize the expected profit of PU. Recent paper [25] adopted the auction strategy to jointly maximize the total satisfaction of all SUs as well as the revenue of PU. Different from [23]- [25] which considered the interference-free model and treated the idle spectrum as a tradable commodity, the authors of [26], [27] considered the interference-cap as a commodity for trading in auction.…”

Section: Introductionmentioning

confidence: 99%

Revenue Sharing Based Resource Allocation for Dynamic Spectrum Access Networks

Zhu

Huang

et al. 2014

IEEE J. Select. Areas Commun.

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Abstract-We propose a revenue sharing based resource allocation scheme for dynamic spectrum access (DSA) networks. In our scheme, based on a mutually agreed revenue sharing scheme, a primary network operator (PNO) actively shares its radio resource with a secondary network operator (SNO), which provides access service to secondary users (SUs) for its revenue maximization. To investigate the coupling effect between the revenue sharing and resource allocation, we formulate the interaction between PNO and SNO as a two-layered game, which includes a top layer game to model their revenue sharing and a bottom layer game to model their joint resource allocations. Specifically, in the top layer, based on their joint resource allocation decisions, the PNO and SNO form a Nash bargaining game to determine the revenue sharing scheme such that both of them can benefit from cooperation satisfactorily. Then, in the bottom layer, under the given revenue sharing scheme, the PNO and SNO form a Stackelberg game to determine their joint resource allocation decisions, which also influence their respective revenues. The two games work iteratively such that the PNO and SNO reach a final equilibrium state at which neither PNO nor SNO will change its decisions unilaterally in both layers. We propose efficient algorithms to solve both the top layer and bottom layer games and compute the final equilibrium of the two-layered game. Specifically, despite the non-convexity of joint resource allocation optimization problem in the bottom layer, we identify its hidden monotonic structure and propose an efficient algorithm, which is based on the polyblock approximation, to achieve the optimal solutions. Moreover, in the top layer, to tackle with the difficulty due to the lack of an analytical objective function for the revenue sharing problem, we explore its hidden unimodal property and propose a Brent's method based algorithm to achieve the optimal solution. Numerical results are presented to verify the performance of our algorithms and show that our revenue sharing based resource allocation scheme yields a winwin situation for the PNO and SNO.

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Auction Based Spectrum Trading for Cognitive Radio Networks

Cited by 25 publications

References 10 publications

Matching theory as enabler of efficient spectrum management in 5G networks

Matching theory as enabler of efficient spectrum management in 5G networks

Preference-Based Spectrum Pricing in Dynamic Spectrum Access Networks

Revenue Sharing Based Resource Allocation for Dynamic Spectrum Access Networks

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