Joint Power and Rate Control in Cognitive Radio Networks: A Game-Theoretical Approach

Zhou, Pan; Yuan, Wei; Liu, Wei; Cheng, Wenqing

doi:10.1109/icc.2008.620

Cited by 60 publications

(57 citation statements)

References 9 publications

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“…Therefore, with (3) and (15), the PU's achievable rate in the j th sub-channel is 2 2 2 2 log (1 (1) (3)) / 3…”

Section: Network Modeling and Notationsmentioning

confidence: 99%

“…In order to address both system efficiency and user fairness issues of CR networks, the authors in [14] proposed a distributed power control strategy by using a cooperative Nash bargaining game model. In [15], a joint power and rate control strategy were presented for SUs on the basis of a cooperative game theoretic framework. Three auction-based schemes were proposed in [16] for multimedia streaming over CR networks.…”

Section: Introductionmentioning

confidence: 99%

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Power Allocation in Primary User-Assisted Multi-Channel Cognitive Radio Networks

Wu¹,

Zhu²

2013

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This paper addresses power allocation problem for spectrum sharing multi-band cognitive radio networks, where the primary user (PU) allows secondary users (SUs) to transmit simultaneously with it by coding SU's signal together with its own signal. The PU acts as the relay for the SUs and sells its transmit power to the SUs to increase its benefit, and the SUs bid for the PU's transmit power for maximizing their utilities. We propose a power allocation scheme based on traditional ascending clock auction, in which the SUs iteratively submit the optimal power demand to the PU according to the PU's announced price, and the PU updates that price based on all SUs' total power demands. Then we mathematically prove the convergence property of the proposed auction algorithm (i.e., the auction algorithm converges in a finite number of clocks), and show that the proposed power auction algorithm can maximize the social welfare. Finally, the performance of the proposed scheme is verified by the simulation results.

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“…Therefore, with (3) and (15), the PU's achievable rate in the j th sub-channel is 2 2 2 2 log (1 (1) (3)) / 3…”

Section: Network Modeling and Notationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power Allocation in Primary User-Assisted Multi-Channel Cognitive Radio Networks

Wu¹,

Zhu²

2013

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“…Further, we decompose the Problem(Relaxed_MINP-i) into three independent sub-problems: Sub-Problem 1: (20) subject to: Constraints (12-13).…”

Section: Problem(relaxed_minp-i)mentioning

confidence: 99%

“…Another distributed approach was presented to jointly consider routing and dynamic spectrum allocation in cognitive radio ad hoc network so that the network throughput is maximized without causing baleful interference to other licensed users [17]. A part of researches investigate to devise energy efficient routing protocols [18][19] or adopt a game-theoretic perspective to handle power control problem in the cognitive radio networks [20][21][22][23].…”

mentioning

confidence: 99%

Distributed energy-efficient cross-layer design for cognitive radio networks

Tseng

Chung

Chen

et al. 2012

2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC)

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Abstract-In this paper, we jointly consider power control, channel assignment, and routing to minimize network energy consumption while maintaining data rate requirements on each radio link in the multi-hop cognitive radio network. This problem is formulated as a Mixed Integer Non-linear Programming (MINP). Due to the NP-hard property of the MINP, the MINP is decomposed into |N| (the number of nodes in the network) problems so that each problem can be distributedly and locally solved at each node. Furthermore, a Lagrangean Relaxation based Heuristic (LRH) was proposed to approximate the solution of each problem. Through the technique of Lagrangean relaxation, each problem is transformed into its relaxed form and solved iteratively. Numerical results demonstrate that the proposed scheme can efficiently save network energy consumption up to 90%.

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“…CR technology promises to improve the network spectrum-utilization efficiency by allowing cognitive secondary users (SUs) to intelligently sense and opportunistically access those spectrum holes temporarily unused by license-holding primary users (PUs). There are two basic spectrum-sharing schemes for coexisting PU and SU networks: One is spectrum overlay, in which SUs detect and avoid overlapping with active PUs in frequency [9], [11], and the other is spectrum underlay, in which SUs spread its transmission over the wide spectrum to lower the transmit power density inflicted on overlapping PUs [12], [14], [15]. In addition, these two spectrum-sharing methods can be interwoven to collect the benefits of both [10].…”

mentioning

confidence: 99%

Optimal Power Control for Cognitive Radio Networks Under Coupled Interference Constraints: A Cooperative Game-Theoretic Perspective

Yang

Tian

2010

IEEE Trans. Veh. Technol.

135

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Abstract-Distributed power control is investigated for cognitive radio networks (CRNs) based on a cooperative gametheoretic framework. Taking into consideration both network efficiency and user fairness, a cooperative Nash bargaining powercontrol game (NBPCG) model is formulated, where interference power constraints (IPCs) are imposed to protect the primary users' (PUs') transmissions, and minimum signal-to-interferenceplus-noise ratio (SINR) requirements are employed to provide reliable transmission opportunities to secondary cognitive users. An SINR-based utility function is designed for this game model, which not only reflects the spectrum efficiency of the CRN but also complies with all the axioms in the Nash theorem and, hence, facilitates efficient algorithmic development.

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Joint Power and Rate Control in Cognitive Radio Networks: A Game-Theoretical Approach

Cited by 60 publications

References 9 publications

Power Allocation in Primary User-Assisted Multi-Channel Cognitive Radio Networks

Power Allocation in Primary User-Assisted Multi-Channel Cognitive Radio Networks

Distributed energy-efficient cross-layer design for cognitive radio networks

Optimal Power Control for Cognitive Radio Networks Under Coupled Interference Constraints: A Cooperative Game-Theoretic Perspective

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