• ETRI Journal
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• v.36 no.2
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• pp.280-285
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• 2014

In this paper, the optimal power control problem in a cooperative relay network is investigated and a new power control scheme is proposed based on a non-cooperative differential game. Optimal power allocated to each node for a relay is formulated using the Nash equilibrium in this paper, considering both the throughput and energy efficiency together. It is proved that the non-cooperative differential game algorithm is applicable and the optimal power level can be achieved.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.25-31
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• 2018

In this paper, we consider the game theoretic approach to investigate the transmit power optimization problem where D2D users share the uplink of the cellular system. Especially, we formulate the transmit power optimization problem as a non cooperative power control game. In the user wide sense, each user may try to select its transmit power level so as to maximize its utility in a selfish way. In the system wide, the transmit power levels of all users eventually converge to the unique point, called Nash Equilibrium. We first formulate the transmit power optimization problem as a non cooperative power control game. Next, we examine the existence of Nash Equilibrium. Finally, we present the numerical example that shows the convergence to the unique transmit power level.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.195-196
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• 2007

The purpose of this paper is to analyze the resource allocation problem in a self organizing network from the viewpoint of game theory. The main focus is to suggest the model and analyze a power control algorithm in wireless ad-hoc networks using non cooperative games. Our approach is based on a model for the level of satisfaction and utility a wireless user in a self organizing network derives from using the system. Using this model, we show a distributed power control scheme that maximizes utility of each user in the network. Formulating this as a non-cooperative game we will show the feasibility of such power control as well as existence of the Nash Equilibrium achieved by the non-cooperative game.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2281-2301
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• 2014

In wireless ad hoc networks the nodes focus on achieving the maximum SINR for efficient data transmission. In order to achieve maximum SINR the nodes culminate in exhausting the battery power for successful transmissions. This in turn affects the successful transmission of the other nodes as the maximum transmission power opted by each node serves as a source of interference for the other nodes in the network. This paper models the choice of power for each node as a non cooperative game where the throughput of the network with respect to the consumption of power is formulated as a utility function. We propose an adaptive pricing scheme that encourages the nodes to use minimum transmission power to achieve target SINR at the Nash equilibrium and improve their net utility in multiuser scenario.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.79-85
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• 2019

We investigate the D2D utility maximization in the cellular system. We focus on the non cooperative game theoretic approach to maximize the individual utility. Cellular system's perspective, interference from the D2D links must be limited to protect the cellular users. To accommodate this interference issue, utility function is first defined to control the individual D2D user's transmit power. More specifically, utility function includes the pricing which limits the individual D2D user's transmit power. Then, non cooperative power game is formulated to maximize the individual utility. Distributed algorithm is proposed to maximize the individual utility, while limiting the interference. Convergence of the proposed distributed algorithm is verified through computer simulation. Also the effect of pricing factor to SIR and interference is provided to show the performance of the proposed distributed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.611-627
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• 2017

For enhancing the coverage of wireless networks and increasing the spectrum efficiency, small cell networks (SCNs) are considered to be one of the most prospective schemes. Most of the existing literature on resource allocation among non-cooperative small cell base stations (SBSs) has widely drawn close attention and there are only a small number of the cooperative ideas in SCNs. Based on the motivation, we further investigate the cooperative approach, which is formulated as a coalition formation game with power control algorithm (CFG-PC). First, we formulate the downlink sub-channel resource allocation problem in an SCN as a coalition formation game. Pareto order and utilitarian order are applied to form coalitions respectively. Second, to achieve more availability and efficiency power assignment, we expand and solve the power control using particle swarm optimization (PSO). Finally, with our proposed algorithm, each SBS can cooperatively work and eventually converge to a stable SBS partition. As far as the transmit rate of per SBS and the system rate are concerned respectively, simulation results indicate that our proposed CFG-PC has a significant advantage, relative to a classical coalition formation algorithm and the non-cooperative case.

• Journal of Communications and Networks
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• v.16 no.2
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.11
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• pp.771-778
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• 2014

We propose Femto-cell power control scheme in HeNet with Game Theory. The Femto-cell which provide high quality with low power is issued by many benefits, however there is a bunch of interferences when many Femto-cells use overlapped bandwidth with Macro-cell. We defined base station of cellular networks and mobile users as players of Game Theory, and configured interference effect among each other as power utility function. Futhermore, we showed enhanced overall system performance, lower power usage and interference decrease by using optimal power.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4188-4206
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• 2016

Power control is widely used to reduce co-channel interference in wireless networks and guarantee the signal-to-interference plus noise ratio (SINR) of ongoing connections. This technique is also effective for wireless body area networks (WBANs). Although achieving satisfactory SINR is important for WBAN users, they may not be willing to achieve it at arbitrarily high power levels since power is a scarce resource in WBANs. Besides, for WBANs with different purposes, the QoS requirements and concern about the power consumption may be different. This motivates us to formulate the power control problem using the concepts from microeconomics and game theory. In this paper, the QoS objective is viewed as a utility function, which represents the degree of user satisfaction, while the power consumption is viewed as a cost function. The power control problem consequently becomes a non-cooperative multiplayer game, in which each player tries to maximize its net utility, i.e., the utility minus the cost. Within this framework, we investigate the Nash equilibrium existence and uniqueness in the game and derive the best response solution to reach the Nash equilibrium. To obtain the optimal transmission power in a distributed way, we further propose a utility-based and QoS-aware power control algorithm (UQoS-PCA). Tunable cost coefficient in UQoS-PCA enables this scheme to be flexible to satisfy diverse service requirements. Simulation results show the convergence and effectiveness of the proposed scheme as well as improvements over existing 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].