• Journal of Communications and Networks
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• 제16권2호
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• pp.183-192
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• 2014

This paper proposes a payment-based power control scheme using non-cooperative game with a novel pricing function in cognitive radio networks (CRNs). The proposed algorithm considers the fairness of power control among second users (SUs) where the value of per SU' signal to noise ratio (SINR) or distance between SU and SU station is used as reference for punishment price setting. Due to the effect of uncertainty fading environment, the system is unable to get the link gain coefficient to control SUs' transmission power accurately, so the quality of service (QoS) requirements of SUs may not be guaranteed, and the existence of Nash equilibrium (NE) is not ensured. Therefore, an alternative iterative scheme with sliding model is presented for the non-cooperative power control game algorithm. Simulation results show that the pricing policy using SUs' SINR as price punishment reference can improve total throughput, ensure fairness and reduce total transmission power in CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권12호
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• pp.2957-2986
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• 2013

The traditional approach of fixed spectrum allocation to licensed networks has resulted in spectrum underutilisation. Cognitive radio technology is envisioned as a promising solution that can be used to resolve the ineffectiveness of the fixed spectrum allocation policy by accessing the underutilised spectrum of existing technologies opportunistically. The implementation of cognitive radio networks (CRNs) faces distinct challenges due to the fact that two systems (i.e., cognitive radio (CR) and primary users (PUs)) with conflicting interests interact with each other. Specially, in self-organised systems such as ad-hoc CRNs (AHCRNs), the coordination of spectrum access introduces challenges to researchers due to rapid utilisation changes in the available spectrum, as well as the multi-hop nature of ad-hoc networks, which creates additional challenges in the analysis of resource allocation (e.g., power control, channel and rate allocation). Instead, game theory has been adopted as a powerful mathematical tool in analysing and modelling the interaction processes of AHCRNs. In this survey, we first review the most fundamental concepts and architectures of CRNs and AHCRNs. We then introduce the concepts of game theory, utility function, Nash equilibrium and pricing techniques. Finally, we survey the recent literature on the game theoretic analysis of AHCRNs, highlighting its applicability to the physical layer PHY, the MAC layer and the network layer.

• 한국위성정보통신학회논문지
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• 제12권4호
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• pp.100-105
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• 2017

이 논문에서는 백스케터 통신에서 악의적인 간섭이 존재할 때, 게임이론을 적용하여 간섭으로부터 회피하고 통신의 성능 최적화를 통한 성능 분석에 관한 내용을 다룬다. 백스케터 통신을 원신호원을 반사하여, 백스케터 신호를 전송하기 때문에 악의적인 간섭에 취약하게 된다. 이를 해결하기 위해 리더-펄로워 관계인 스텔켈베르그 게임이론을 적용하며, 라그랑지안 승수 방법을 통해 최적화를 수행한다. 또한, 네쉬 게임이론과 스텔켈베르그 두 가지 게임이론을 백스케터 통신에 적용하고 적용된 게임이론에 따른 백스케터 통신의 간섭 회피 성능을 비교 분석을 수행한다. 본 논문의 시뮬레이션을 통해 스텔켈베르그 게임이론이 악의적인 간섭 회피에서 더 나은 성능을 보임을 증명하고, 백스케터의 통신 최적의 성능과 스텔켈베르그 게임 균형을 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2709-2734
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• 2020

The growing demand to make wireless data services 5G compatible has necessitated the development of an energy-efficient approach for an effective new wireless environment. In this paper, we first propose a cognitive sensor node (CSN) based game theory for deriving energy via a primary user-transmitted radio frequency signal. Cognitive users' time was segmented into three phases based on a time switching protocol: energy harvest, spectrum sensing and data transmission. The proposed model chooses the optimal energy-harvesting phase as the effected factor. We further propose a distributed energy-harvesting model as a utility function via pricing techniques. The model is a non-cooperative game where players can increase their net benefit in a selfish manner. Here, the price is described as a function pertaining to transmit power, which proves that the proposed energy harvest game includes Nash Equilibrium and is also unique. The best response algorithm is used to achieve the green connection between players. As a result, the results obtained from the proposed model and algorithm show the advantages as well as the effectiveness of the proposed study. Moreover, energy consumption was reduced significantly (12%) compared to the benchmark algorithm because the proposed algorithm succeeded in delivering energy in micro which is much better compared to previous studies. Considering the reduction and improvement in power consumption, we could say the proposed model is suitable for the next wireless environment represented in 5G.