• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.34-49
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• 2015

Market means of spectrum trading have been utilized as a vital method of spectrum sharing and access in future cognitive radio system. In this paper, we consider the spectrum trading with multiple primary carrier providers (PCP) leasing the spectrum to multiple secondary carrier providers (SCP) for a short period of time. Several factors including the price of the resource, duration of leasing, and the spectrum quality guides the proposed model. We formulate three trading policies based on the game theory for dynamic spectrum access in a LTE based cognitive radio system (CRS). In the first, we consider utility function based resource sharing (UFRS) without any knowledge of past transaction. In the second policy, each SCP deals with PCP using a non-cooperative resource sharing (NCRS) method which employs optimal strategy based on reinforcement learning. In variation of second policy, third policy adopts a Nash bargaining while incorporating a recommendation entity in resource sharing (RERS). The simulation results suggest overall increase in throughput while maintaining higher spectrum efficiency and fairness.

• Korean Management Science Review
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• v.23 no.3
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• pp.243-257
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• 2006

ITU-T's NgN(Next generation Network) architecture is expected to offer a new Internet platforms such as QoS(Quality of Service) guaranteed services as it overcame the limitations of the existing best-effort Internet architecture. However, policy development crucial for the NgN framework(e.g., interconnections and billing) is lagging far behind technology development. For example, arguments over network neutrality clearly indicate little understanding of the Internet industry structure where diverse providers including ISP and CP coexist. This study employs a network economics approach to predict how the competitive landscape involving various providers will evolve under the traffic-based billing system under the NgN environment. Applied is the non-cooperative game theory, in particular, Stackelberg's repeated game in order to build and analyze model for competition among those providers. We also studied possible impacts that CPs would have on the competitive landscape if they have an option to replace ISP: i.e., CDN(Content Delivery Network) provider. Lastly, based on the model analysis and experiments, presented are their implications to policy development and tile future prospect.

• 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.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.49-55
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• 2015

In cognitive radio network (CRN), spectrum sensing is an elementary level of technology for non-interfering to licensed user. Required sample number for spectrum sensing is directly related to the throughput of secondary user and makes the tradeoff between the throughput of secondary user and interference to primary user. Required spectrum sensing sample is derived from required false alarm, detection probability and minimum required SNR of primary user (PU). If we make clustering and minimize the required transmission boundary of secondary user (SU), we can relax the required PU SNR for spectrum sensing because the required SNR for PU signal sensing is related to transmission range of SU. Therefore we can achieve efficient throughput of CRN by minimizing spectrum sensing sample. For this, we design the tradeoff between gain and loss could be obtained from clustering, according to the size of cluster members through game theory and simulation results confirm the effectiveness of the proposed method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.71-82
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• 2009

As a solution to spectrum under-utilization problem, Cognitive radio (CR) introduces a dynamic spectrum access technology. In the area, one of the most important problems is how secondary users (SUs) should choose between the available channels, which means how to achieve load balancing between channels. We consider spectrum load balancing problem for CR system in frequency domain and especially in time domain. Our objective is to balance the load among the channels and balance the occupied time length of slots for a fixed channel dynamically in order to obtain a user-optimal solution. In frequency domain, we refer to Dynamic Noncooperative Scheme with Communication (DNCOOPC) used in distributed system and a distributed Dynamic Spectrum Load Balancing algorithm (DSLB) is formed based on DNCOOPC. In time domain, Spectrum Load Balancing method with QoS support is proposed based on Dynamic Feed Back theory and Hash Table (SLBDH). The performance of DSLB and SLBDH are evaluated. In frequency domain, DSLB is more efficient compared with existing Compare_And_Balance (CAB) algorithm and gets more throughput compared with Spectrum Load Balancing (SLB) algorithm. Also, DSLB is a fair scheme for all devices. In time domain, SLBDH is an efficient and precise solution compared with Spectrum Load Smoothing (SLS) method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.591-593
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• 2016

Device-to-device (D2D) communications underlaid cellular infrastructure is an competitive local area services technology to promote spectrum usage for next generation cellular networks. These potential can only be tap through efficient interference coordination. Previous works only concentrated on interference from D2D pairs whiles interference from CUs to D2D pairs were neglected. This work focus on solving uplink interference problem emanating from multiple CUs sharing its resource with multiple D2D pairs. The base station (BS) acting as a supervisor selfishly institute a pricing scheme to manage the interference it experience from D2D pairs based on its Quality of service (QoS) requirement. D2D pairs following the supervisor make power allocation decisions considering the price from the BS in a non-cooperative game fashion. In order for the D2D pairs to also meet their QoS requirement, they suggest a price to the BS called discount price which reflects the interference they receive from the CUs. Finally, we analyze the proposed approach.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.10-20
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• 2024

The conservation and restoration of wetlands are essential tasks for the sustainable development of human society and the environment, providing vital benefits such as biodiversity maintenance, natural disaster mitigation, and climate change alleviation. This study aims to analyze the strategic interactions and interests among various stakeholders using game theory and to provide significant grounds for policy decisions related to wetland restoration and development. In this study, hypothetical scenarios were set up for three types of cities: large, medium, and small. Stakeholders such as governments, development companies, environmental groups, and local residents were identified. Strategic options for each stakeholder were developed, and a payoff matrix was established through discussions among wetland ecology experts. Subsequently, non-cooperative game theory was applied to analyze Nash equilibria and Pareto efficiency. In large cities, strategies of 'Wetland Conservation' and 'Eco-Friendly Development' were found beneficial for all stakeholders. In medium cities, various strategies were identified, while in small cities, 'Eco-Friendly Development' emerged as the optimal solution for all parties involved. The Pareto efficiency analysis revealed how the optimal solutions for wetland management could vary across different city types. The study highlighted the importance of wetland conservation, eco-friendly development, and wetland restoration projects for each city type. Accordingly, policymakers should establish regulations and incentives that harmonize environmental protection and urban development and consider programs that promote community participation. Understanding the roles and strategies of stakeholders and the advantages and disadvantages of each strategy is crucial for making more effective policy decisions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.543-552
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• 2013

For the safety messages in IEEE 802.11p/WAVE vehicles network environment, strict periodic beacon broadcasting requires status advertisement to assist the driver for safety. In crowded networks where beacon message are broadcasted at a high number of frequencies by many vehicles, which used for beacon sending, will be congested by the wireless medium due to the contention-window based IEEE 802.11p MAC. To resolve the congestion, we consider a MAC scheme based on slotted p-persistent CSMA as a simple non-cooperative Bayesian game which involves payoffs reflecting the attempt probability. Then, we derive Bayesian Nash Equilibrium (BNE) in a closed form. Using the BNE, we propose new congestion control algorithm to improve the performance of the beacon rate under saturation condition in IEEE 802.11p/WAVE vehicular networks. This algorithm explicitly computes packet delivery probability as a function of contention window (CW) size and number of vehicles. The proposed algorithm is validated against numerical simulation results to demonstrate its stability.