• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1379-1397
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• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.403-405
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• 2000

This paper presents a N-player game theory application for analyzing power transactions in a deregulated energy marketplace such as PoolCo, where, participants, especially, generating entities, maximize their net profits through optimal bidding strategies (i.e., bidding prices and bidding generations). In this paper, the electricity market for power transactions is modeled as a non-cooperative. N-player game with complete information, where the solution is determined in a continuous strategy domain having recourse to the Nash equilibrium idea.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.85-92
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• 2005

In this paper, Nash equilibriums of generation markets are investigated using a game theory application for simplified competitive electricity markets. We analyze the characteristics of equilibrium states in N-company spot markets modeled by uniform pricing auctions and propose a new method for obtaining Nash equilibriums of the auction. We assume that spot markets are operated as uniform pricing auctions and that each generation company submits its bids into the auction in the form of a seal-bid. Depending on the bids of generation companies, market demands are allocated to each company accordingly. The uniform pricing auction in this analysis can be formulated as a non-cooperative and static game in which generation companies correspond to players of the game. The coefficient of the bidding function of company-n is the strategy of player-n (company-n) and the payoff of player-n is defined as its profit from the uniform price auction. The solution of this game can be obtained using the concept of the non-cooperative equilibrium originating from the Nash idea. Based on the so called residual demand curve, we can derive the best response function of each generation company in the uniform pricing auction with N companies, analytically. Finally, we present an efficient means to obtain all the possible equilibrium set pairs and to examine their feasibilities as Nash equilibriums. A simple numerical example with three generation companies is demonstrated to illustrate the basic idea of the proposed methodology. From this, we can see the applicability of the proposed method to the real-world problem, even though further future analysis is required.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.11
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• pp.1429-1436
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• 2013

This study presents an approach for designing a vehicle rollover prevention controller using differential game theory and multi-level programming. The rollover prevention problem can be modeled as a non-cooperative zero-sum two-player differential game. A controller as an equilibrium solution of the differential game guarantees the worst-case performance against every possible steering input. To obtain an equilibrium solution to the differential game with a small amount of computational effort, a multi-level programming approach with a relaxation procedure is used. To cope with the loss of maneuverability caused by the active suspension, an electronic stability program (ESP) is adopted. Through simulations, the proposed method is shown to be effective in obtaining an equilibrium solution of the differential game.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.4
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• pp.1-9
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• 2015

This paper proposes CAC method that is more efficient for RRM using game theory combined with Multiple Attribute Decision Making(MADM). Because users request services with different Quality of Service(QoS), the network preference values to alternative networks for each service are calculated by MADM methods such as Grey Relational Analysis(GRA), Simple Additive Weighting(SAW) and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS). According to a utility function representing preference value, non-cooperative game is played, and then network provider select the requested service that provide maximum payoff. The appropriate service is selected through Nash Equilibrium that is the solution of game and the game is played repeated. We analyze two overlaid networks among four Wireless LAN(WLAN) systems with different properties. Simulation results show that proposed MADM techniques have same outcomes for every game round.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.113-114
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• 2017

본 논문에서는 셀룰라시스템의 상향링크 자원을 사용하는 D2D 단말의 전송전력 최적화문제를 게임이론적 방법으로 고찰해본다. 먼저, 전송전력 최적화문제를 비협력적 전송전력게임으로 구성하고, 구성된 전송전력게임이 나쉬 평형을 가지게 됨을 확인한다. 본 논문에서 도출된 나쉬 평형에서는 개별 D2D 단말은 오로지 자신의 전송전력을 최적화하도록 전송전력값을 선택한다. 하지만, 시스템 입장에서는 결국 모든 단말의 전송전력값은 나쉬평형이라고 하는 전송전력의 유일한 수렴점에 도달하게 된다. 컴퓨터실험을 통하여 다수 개의 D2D 사용자 환경에서 나쉬평형이 존재함을 확인한다.

• ETRI Journal
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• v.34 no.2
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• pp.159-167
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• 2012

In this paper, a new distributed resource allocation algorithm is proposed to alleviate the cross-tier interference for orthogonal frequency division multiplexing access macrocell and femtocell overlay. Specifically, the resource allocation problem is modeled as a non-cooperative game. Based on game theory, we propose an iterative algorithm between subchannel and power allocation called distributed resource allocation which requires no coordination among the two-hierarchy networks. Finally, a macrocell link quality protection process is proposed to guarantee the macrocell UE's quality of service to avoid severe cross-tier interference from femtocells. Simulation results show that the proposed algorithm can achieve remarkable performance gains as compared to the pure waterfilling algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2631-2649
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• 2021

Device-to-Device (D2D) communication is one of the enabling technologies for 5G networks that support proximity-based service (ProSe) for wireless network communications. This paper proposes a power control algorithm based on the Nash equilibrium and game theory to eliminate the interference between the cellular user device and D2D links. This leadsto reliable connectivity with minimal power consumption in wireless communication. The power control in D2D is modeled as a non-cooperative game. Each device is allowed to independently select and transmit its power to maximize (or minimize) user utility. The aim is to guide user devices to converge with the Nash equilibrium by establishing connectivity with network resources. The proposed algorithm with pricing factors is used for power consumption and reduces overall interference of D2Ds communication. The proposed algorithm is evaluated in terms of the energy efficiency of the average power consumption, the number of D2D communication, and the number of iterations. Besides, the algorithm has a relatively fast convergence with the Nash Equilibrium rate. It guarantees that the user devices can achieve their required Quality of Service (QoS) by adjusting the residual cost coefficient and residual energy factor. Simulation results show that the power control shows a significant reduction in power consumption that has been achieved by approximately 20% compared with algorithms in [11].

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.1
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• pp.53-58
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• 2012

With a game-theoretic view, p-persistence slotted ALOHA is structured as a non-cooperative game, in which a Nash equilibrium is sought to provide a value for the probability of attempting to deliver a packet. An expression of Nash equilibrium necessarily includes the number of active outer stations, which is hardly available in many practical applications. In this paper, we thus propose a Bayesian scheme of predicting the number of active outer stations prior to deciding whether to attempt to deliver a packet or not. Despite only requiring the minimal information that an outer station is genetically able to acquire by itself, the Bayesian scheme demonstrates the competitive predicting performance against a method which depends on heavy information.