A New Game Algorithm for Power Control in Cognitive Radio Networks

Li, Feng; Tan, Xuezhi; Wang, Li

doi:10.1109/tvt.2011.2172474

Cited by 44 publications

(30 citation statements)

References 18 publications

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“…They proposed a Nash game model, in which the cost function is defined as a weighted sum of power and square of signal-to-interference-and-noise-ratio (SINR) error. On the other hand, the authors of [12] proposed a new power control game based on the cost function and the target of transmit power, which has been included as well as the target SINR. The cost function in [12] is defined as a weighted sum of the Logarithm of SINR error and the Logarithm function of power error.…”

Section: Related Workmentioning

confidence: 99%

Non-Cooperative Power Control Game in D2D Underlying Networks with Variant System Conditions

et al. 2019

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In this paper, the problem of power control using a game theoretic approach based on sigmoid cost function is studied for device-to-device (D2D) communications underlying cellular networks. A non-cooperative game, where each D2D transmitter and a cellular user select their own transmit power level independently, is analyzed to minimize their user-serving cost function and achieve a target signal to interference-plus-noise-ratio (SINR) requirement. It is proved analytically that the Nash equilibrium point of the game exists and it is unique under certain constraints. Numerical results verify the analysis and demonstrate the effectiveness of the proposed game with variant system conditions, such as path loss exponents, target SINR, interference caused by the cellular user, pricing coefficients, and sigmoid control parameter.

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Section: Related Workmentioning

confidence: 99%

Non-Cooperative Power Control Game in D2D Underlying Networks with Variant System Conditions

et al. 2019

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“…Cognitive radio which is based on dynamic spectrum access has attracted more and more attention of academy and engineering in recent years [5,6]. Various kinds of emerging network technologies have begun to adopt dynamic spectrum detection and dynamic spectrum access to improve the efficiency of spectrum utilization.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Spectrum Pricing with Secondary User’s Normal Demand Preference

Wang

2018

Mobile Information Systems

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During secondary user's dynamic access to authorized spectrum, a key issue is how to ascertain an appropriate spectrum price so as to maximize primary system's benefit and satisfy secondary user's diverse spectrum demands. In this paper, a scheme of pricing-based dynamic spectrum access is proposed. According to the diverse qualities of idle spectrum, the proposed scheme applies a Hotelling game model to form the spectrum pricing problem. Firstly, establish a model of spectrum leasing, among which the idle spectrum with different qualities constitutes a spectrum pool. en, divide the idle spectrum into equivalent width of leased channels, which will be uniformly sold in order. Secondary users can choose proper channels to purchase in the spectrum pool according to their spectrum usage preferences which are subject to normal distribution and affected by the spectrum quality along with market estimation. is paper analyzes the effect of spectrum pricing according to the primary system's various tendencies to spectrum usage and economic income. Numerical results evaluate the effectiveness of the proposed pricing method in improving the primary system's profits.

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“…It is more flexible and fair than other methods, because it can set up a specific utility function for each CU accordingly in a specific power control scheme, such as to maximize the CRS capacity, to reduce the energy consumption, or to reduce the algorithm complexity, etc. Authors in [3] imported the power threshold to iterative algorithm using game theory in the CRS to achieve a better anti-noise performance and a lower system complexity. Reference [4] proposed a new iterative algorithm under flat-fading environment to meet the fairness among CUs.…”

Section: Introductionmentioning

confidence: 99%

A Novel Power Control Algorithm for Massive MIMO Cognitive Radio Systems Based on Game Theory

Cui

et al. 2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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In this paper, a novel system model named as massive multiple-input multiple-output (MIMO) cognitive radio system (CRS) is built and an efficient uplink power control algorithm based on noncooperative game theory with a selfadaptive power threshold scheme is proposed to improve the power efficiency. And then, we give an analytical model for the massive MIMO CRS and the detail of the self-adaptive power threshold scheme. Moreover, we prove the existence of the Nash Equilibrium and the convergence of the proposed algorithm. To evaluate the performance of the proposed algorithm, we do simulations and compare the system performance with two other classical power control algorithms. Simulation results demonstrate that the proposed algorithm can achieve a preferable performance in signal-to-noise-plus interference ratio (SINR) and a higher utility with lower transmission power and faster convergence. It implies that the novel way can achieve higher power efficiency and a better overall system performance.

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A New Game Algorithm for Power Control in Cognitive Radio Networks

Cited by 44 publications

References 18 publications

Non-Cooperative Power Control Game in D2D Underlying Networks with Variant System Conditions

Non-Cooperative Power Control Game in D2D Underlying Networks with Variant System Conditions

Dynamic Spectrum Pricing with Secondary User’s Normal Demand Preference

A Novel Power Control Algorithm for Massive MIMO Cognitive Radio Systems Based on Game Theory

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