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Susumu Yoshida - One of the best experts on this subject based on the ideXlab platform.
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Potential Game approach for self organization scheme in open access heterogeneous networks
2011 6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2011Co-Authors: Wayan I Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:In the present paper, a self-organization scheme for joint base station selection and resource block allocation in an OFDMA cellular network is proposed. The network consists of overlaying macrocell and indoor picocells with open access configuration. Inspired by the cognitive radio technology, each mobile user in heterogeneous network selects the most appropriate base station and allocates resource blocks in a decentralized fashion in order to manage the cross- and co-tier interference, and improve the throughput performance. The problem is formulated as a Potential Game, which is demonstrated to converge to a Nash equilibrium when distributed sequential play based on the best response dynamics is adopted. The simulation results show that the proposed self-organization scheme improves the uplink system capacity of the heterogeneous networks with a slight loss of the picocell performance.
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Potential Game approach for self organized interference management in closed access femtocell networks
Vehicular Technology Conference, 2011Co-Authors: Wayan I Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:This paper proposes a Game-theoretic approach for self-organized resource allocation in OFDMA femtocells with closed access configuration. The objective of the proposed scheme is to overcome the interference problem caused by co-channel operation of femtocells in an existing macrocell network using a self-organization capability of femto users. Inspired by the emerging cognitive radio technology, each femto user acts as an autonomous entity and attempts to select the most appropriate subset of resource blocks in a decentralized manner in order to mitigate the cross- and co-tier interference. Such a self-organized resource allocation scheme can be modeled as a Potential Game, which guarantees the convergence to a Nash equilibrium as long as distributed sequential play based on the best response strategy is adopted. Simulation results show that the proposed scheme improves the capacity of the femtocell network, while minimizing the performance degradation of the macrocell network.
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CrownCom - Potential Game approach for self-organization scheme in open access heterogeneous networks
Proceedings of the 6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2011Co-Authors: I Wayan Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:In the present paper, a self-organization scheme for joint base station selection and resource block allocation in an OFDMA cellular network is proposed. The network consists of overlaying macrocell and indoor picocells with open access configuration. Inspired by the cognitive radio technology, each mobile user in heterogeneous network selects the most appropriate base station and allocates resource blocks in a decentralized fashion in order to manage the cross- and co-tier interference, and improve the throughput performance. The problem is formulated as a Potential Game, which is demonstrated to converge to a Nash equilibrium when distributed sequential play based on the best response dynamics is adopted. The simulation results show that the proposed self-organization scheme improves the uplink system capacity of the heterogeneous networks with a slight loss of the picocell performance.
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spectrum sharing with interference management for distributed cognitive radio networks a Potential Game approach
Vehicular Technology Conference, 2010Co-Authors: Wayan I Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:In the present paper, a Game theoretic framework of joint channel selection and power allocation for spectrum sharing in distributed cognitive radio networks is proposed. The objective of the proposed scheme is to investigate the performance of the lower- priority system in spectrum sharing where the lower-priority users utilize the spectrum by selecting the channel and transmit power while aware of the interference to the higher-priority users. The utility function that captures the cooperative behavior to minimize the interference and the satisfaction to improve the throughput is defined. The proposed joint channel selection and power allocation Game can be formulated as a Potential Game and it is guaranteed to converge to a Nash equilibrium when the best response dynamic is performed. The simulation results verify the convergence of the proposed Potential Game and reveal that the proposed utility function with coefficient adjustment improves the throughput performance of the lower-priority system compared to that of without coefficient adjustment, while ensuring the Quality of Service (QoS) constraint at the higher-priority system.
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Potential Game Approach for Spectrum Sharing in Distributed Cognitive Radio Networks
IEICE Transactions on Communications, 2010Co-Authors: I Wayan Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:In a spectrum sharing system, lower-priority users are allowed to spatially reuse the spectrum allocated to higher-priority users as long as they do not disrupt communications of the latter. Therefore, to improve spectrum utilization, an important requirement for the former users is to manage the interference and ensure that the latter users can maintain reliable communications. In the present paper, a Game theoretic framework of joint channel selection and power allocation for spectrum sharing in distributed cognitive radio networks is proposed. First, a utility function that captures the cooperative behavior to manage the interference and the satisfaction level to improve the throughput of the lower-priority users is defined. Next, based on the defined utility function, the proposed framework can be formulated as a Potential Game; thus, it is guaranteed to converge to a Nash equilibrium when the best response dynamic is performed. Simulation results show the convergence of the proposed Potential Game and reveal that performance improvements in terms of network throughput of the lower-priority users and outage probability of the higher-priority users can be achieved by the introduction of an adaptive coefficient adjustment scheme in the proposed utility function at the expense of the convergence to the Nash equilibrium
Koji Yamamoto - One of the best experts on this subject based on the ideXlab platform.
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CCNC - Starvation mitigation for dense WLANs through distributed channel selection: Potential Game approach
2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2017Co-Authors: Bo Yin, Shotaro Kamiya, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura, Hirantha AbeysekeraAbstract:A Potential Game based distributed channel selection scheme is proposed in this paper to mitigate the flow-in-the-middle (FIM) throughput starvation problem that frequently occurs in dense wireless local area networks (WLANs). The FIM throughput starvation occurs when neighbors of a given node are not within the carrier sense ranges of each other. Since they spatially reuse the channel and at least one of them transmits with a high probability, the node in the middle would detect the channel being occupied for a prolonged time and therefore experience extremely low throughput. The basic idea of the proposed scheme is to let each access point (AP) select the channel that reduces the number of three-node chain topologies on its two-hop neighborhood contention graph. The proposed scheme is proved to be a Potential Game, i.e., the proposed scheme is guaranteed to converge. Graph-based simulation shows that starvation occurs on 20% of nodes when nodes randomly select their frequency channels. The proposed scheme significantly reduces the number of starved nodes along with iterations, outperforming the compared traditional Potential Game based scheme.
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A Comprehensive Survey of Potential Game Approaches to Wireless Networks
IEICE Transactions on Communications, 2015Co-Authors: Koji YamamotoAbstract:Potential Games form a class of non-cooperative Games where the convergent of unilateral improvement dynamics is guaranteed in many practical cases. The Potential Game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of Potential Games are introduced, and Games in wireless networks that have been proven to be Potential Games are comprehensively discussed
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Potential Game approach for self organization scheme in open access heterogeneous networks
2011 6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2011Co-Authors: Wayan I Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:In the present paper, a self-organization scheme for joint base station selection and resource block allocation in an OFDMA cellular network is proposed. The network consists of overlaying macrocell and indoor picocells with open access configuration. Inspired by the cognitive radio technology, each mobile user in heterogeneous network selects the most appropriate base station and allocates resource blocks in a decentralized fashion in order to manage the cross- and co-tier interference, and improve the throughput performance. The problem is formulated as a Potential Game, which is demonstrated to converge to a Nash equilibrium when distributed sequential play based on the best response dynamics is adopted. The simulation results show that the proposed self-organization scheme improves the uplink system capacity of the heterogeneous networks with a slight loss of the picocell performance.
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Potential Game approach for self organized interference management in closed access femtocell networks
Vehicular Technology Conference, 2011Co-Authors: Wayan I Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:This paper proposes a Game-theoretic approach for self-organized resource allocation in OFDMA femtocells with closed access configuration. The objective of the proposed scheme is to overcome the interference problem caused by co-channel operation of femtocells in an existing macrocell network using a self-organization capability of femto users. Inspired by the emerging cognitive radio technology, each femto user acts as an autonomous entity and attempts to select the most appropriate subset of resource blocks in a decentralized manner in order to mitigate the cross- and co-tier interference. Such a self-organized resource allocation scheme can be modeled as a Potential Game, which guarantees the convergence to a Nash equilibrium as long as distributed sequential play based on the best response strategy is adopted. Simulation results show that the proposed scheme improves the capacity of the femtocell network, while minimizing the performance degradation of the macrocell network.
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CrownCom - Potential Game approach for self-organization scheme in open access heterogeneous networks
Proceedings of the 6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2011Co-Authors: I Wayan Mustika, Koji Yamamoto, Hidekazu Murata, Susumu YoshidaAbstract:In the present paper, a self-organization scheme for joint base station selection and resource block allocation in an OFDMA cellular network is proposed. The network consists of overlaying macrocell and indoor picocells with open access configuration. Inspired by the cognitive radio technology, each mobile user in heterogeneous network selects the most appropriate base station and allocates resource blocks in a decentralized fashion in order to manage the cross- and co-tier interference, and improve the throughput performance. The problem is formulated as a Potential Game, which is demonstrated to converge to a Nash equilibrium when distributed sequential play based on the best response dynamics is adopted. The simulation results show that the proposed self-organization scheme improves the uplink system capacity of the heterogeneous networks with a slight loss of the picocell performance.
Maria Canales - One of the best experts on this subject based on the ideXlab platform.
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A dynamic access point allocation algorithm for dense wireless LANs using Potential Game
Computer Networks, 2020Co-Authors: Alessandro Raschella, Faycal Bouhafs, Michael Mackay, Qi Shi, Jorge Ortin, José Ramón Gállego, Maria CanalesAbstract:Abstract This work introduces an innovative Access Point (AP) allocation algorithm for dense Wi-Fi networks, which relies on a centralised Potential Game developed in a Software-Defined Wireless Networking (SDWN)-based framework. The proposed strategy optimises the allocation of the Wi-Fi stations (STAs) to APs and allows their dynamic reallocation according to possible changes in the capacity of the Wi-Fi network. This paper illustrates the design of the proposed framework based on SDWN and the implementation of the Potential Game-based algorithm, which includes two possible strategies. The main novel contribution of this work is that the algorithm allows us to efficiently reallocate the STAs by considering external interference, which can negatively affect the capacities of the APs handled by the SDWN controller. Moreover, the paper provides a detailed performance analysis of the algorithm, which describes the significant improvements achieved with respect to the state of the art. Specifically, the results have been compared against the AP selection considered by the IEEE 802.11 standards and another centralised algorithm dealing with the same problem, in terms of the data bit rate provided to the STAs, their dissatisfaction and Quality of Experience (QoE). Finally, the paper analyses the trade-off between efficient performance and the computational complexity achieved by the strategies implemented in the proposed algorithm.
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ap selection algorithm based on a Potential Game for large ieee 802 11 wlans
Network Operations and Management Symposium, 2018Co-Authors: Alessandro Raschella, Faycal Bouhafs, Michael Mackay, Qi Shi, Jorge Ortin, José Ramón Gállego, Maria CanalesAbstract:This paper presents a novel Access Point (AP) selection strategy based on a Potential Game played at a centralized controller. The proposed approach relies on Software Defined Networking (SDN), which has long been considered in the literature as a method to control management functionalities for Wi-Fi networks. The use of SDN provides a global view of the network, which guarantees an efficient distribution of Wi-Fi users among the APs. The centralized Potential Game proposed in this paper is based on the Fittingness Factor (FF) concept, which is a metric reflecting the suitability of the available spectrum resources to the application requirements. This paper describes the development of a new SDN-based framework that implements the Potential Game-based algorithm relying on the FF for efficient AP selection. The simulation campaign illustrates the important gains, both in terms of data rates assigned to the Wi-Fi users and their satisfaction compared against the AP selection suggested by the IEEE 802.11 standards and another algorithm proposed in the literature.
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NOMS - AP selection algorithm based on a Potential Game for large IEEE 802.11 WLANs
NOMS 2018 - 2018 IEEE IFIP Network Operations and Management Symposium, 2018Co-Authors: Alessandro Raschella, Faycal Bouhafs, Michael Mackay, Qi Shi, Jorge Ortin, José Ramón Gállego, Maria CanalesAbstract:This paper presents a novel Access Point (AP) selection strategy based on a Potential Game played at a centralized controller. The proposed approach relies on Software Defined Networking (SDN), which has long been considered in the literature as a method to control management functionalities for Wi-Fi networks. The use of SDN provides a global view of the network, which guarantees an efficient distribution of Wi-Fi users among the APs. The centralized Potential Game proposed in this paper is based on the Fittingness Factor (FF) concept, which is a metric reflecting the suitability of the available spectrum resources to the application requirements. This paper describes the development of a new SDN-based framework that implements the Potential Game-based algorithm relying on the FF for efficient AP selection. The simulation campaign illustrates the important gains, both in terms of data rates assigned to the Wi-Fi users and their satisfaction compared against the AP selection suggested by the IEEE 802.11 standards and another algorithm proposed in the literature.
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Potential Game for joint channel and power allocation in cognitive radio networks
Electronics Letters, 2010Co-Authors: Maria Canales, José Ramón GállegoAbstract:Presented is a Game theoretic solution for joint channel and power allocation in cognitive radio networks. This issue has been previously addressed, but the proposed Games assume a global knowledge of the players' strategies, which make the solution not scalable. In contrast, here the problem is formulated as a Potential Game only requiring local information. The obtained results are compared with a metaheuristic genetic algorithm to show the correctness of the proposal.
Robert J Marks - One of the best experts on this subject based on the ideXlab platform.
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common control channel assignment in cognitive radio networks using Potential Game theory
Wireless Communications and Networking Conference, 2013Co-Authors: Yanqing Liu, Liang Dong, Robert J MarksAbstract:In a cognitive radio network, it is indispensable to assign common control channels for group operations of the secondary users of the spectrum. The assignment requires that multiple secondary users establish the least amount of frequency channels among them while each chooses a channel that has minimum interference to its nearby primary users. We model this problem as a strategic Game and design its utility function such that the Game is a Potential Game. A set of pure Nash equilibria are found by locating the local optima of the Potential function. We develop sequential and asynchronous updates of Game players' strategies using the best response dynamic. In order for the search to escape the local optimum and reach the global optimum of the Potential function, we adopt simulated annealing in the sequential and asynchronous updates of the strategies. The optimal assignment of the common control channel is obtained accordingly and the convergence property is analyzed for these updating schemes.
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WCNC - Common control channel assignment in cognitive radio networks using Potential Game theory
2013 IEEE Wireless Communications and Networking Conference (WCNC), 2013Co-Authors: Yanqing Liu, Liang Dong, Robert J MarksAbstract:In a cognitive radio network, it is indispensable to assign common control channels for group operations of the secondary users of the spectrum. The assignment requires that multiple secondary users establish the least amount of frequency channels among them while each chooses a channel that has minimum interference to its nearby primary users. We model this problem as a strategic Game and design its utility function such that the Game is a Potential Game. A set of pure Nash equilibria are found by locating the local optima of the Potential function. We develop sequential and asynchronous updates of Game players' strategies using the best response dynamic. In order for the search to escape the local optimum and reach the global optimum of the Potential function, we adopt simulated annealing in the sequential and asynchronous updates of the strategies. The optimal assignment of the common control channel is obtained accordingly and the convergence property is analyzed for these updating schemes.
Han-lim Choi - One of the best experts on this subject based on the ideXlab platform.
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Potential Game-Based Non-Myopic Sensor Network Planning for Multi-Target Tracking
IEEE Access, 2018Co-Authors: Su-jin Lee, Soon-seo Park, Han-lim ChoiAbstract:This paper presents a Potential Game-based method for the non-myopic planning of mobile sensor networks in the context of target tracking. The planning objective is to select the sequence of sensing points over more than one future time step to maximize information about the target states. This multi-step lookahead scheme aims to overcome getting trapped at local information maximum when there are gaps in the sensing coverage due to constraints of the sensor platform mobility or limitations in sensing capabilities. However, long-term planning becomes computationally intractable as the length of planning horizon increases. This paper develops a Game-theoretic approach to address the computational challenges. The main contributions of this paper are twofold: 1) to formulate a non-myopic planning problem for tracking multiple targets in a Potential Game, the size of which increases linearly as the number of planning steps and 2) to design a learning algorithm exploiting the joint strategy fictitious play and dynamic programming, which overcomes the gaps in sensing coverage. The numerical examples of multi-target tracking demonstrate that the proposed method gives a better estimation performance than myopic planning and is computationally tractable.
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Efficient sensor network planning method using approximate Potential Game.
arXiv: Computer Science and Game Theory, 2017Co-Authors: Su-jin Lee, Youngjin Park, Han-lim ChoiAbstract:This paper addresses information-based sensing point selection from a set of possible sensing locations, which determines a set of measurement points maximizing the mutual information between the sensor measurements and the variables of interest. A Potential Game approach has been applied to addressing distributed implementation of decision making for cooperative sensor planning. When a sensor network involves a large number of sensing agents, the local utility function for a sensing agent is hard to compute, because the local utility function depends on the other agents' decisions while each sensing agent is inherently faced with limitations in both its communication and computational capabilities. Accordingly, a local utility function for each agent should be approximated to accommodate limitations in information gathering and processing. We propose an approximation method for a local utility function using only a portion of the decisions of other agents. The part of the decisions that each agent considers is called the neighboring set for the agent. The error induced by the approximation is also analyzed, and to keep the error small we propose a neighbor selection algorithm that chooses the neighbor set for each agent in a greedy way. The selection algorithm is based on the correlation information between one agent's measurement selection and the other agents' selections. Futhermore, we show that a Game with an approximate local utility function has an $\epsilon$-equilibrium and the set of the equilibria include the Nash equilibrium of the original Potential Game. We demonstrate the validity of our approximation method through two numerical examples on simplified weather forecasting and multi-target tracking.
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DARS - Potential Game-Theoretic Analysis of a Market-Based Decentralized Task Allocation Algorithm
Springer Tracts in Advanced Robotics, 2016Co-Authors: Han-lim Choi, Keumseong Kim, Luke B Johnson, Jonathan P HowAbstract:This paper presents a Potential Game-theoretic interpretation and analysis of a decentralized task allocation algorithm, consensus-based bundled algorithm, which was developed by the authors’ prior work. It is, in particular, proved that the consensus-based bundle algorithm converges to a pure strategy Nash equilibrium of some distributed welfare Game, and the price of anarchy and the price of stability of this equilibrium are 1/2 and 1, respectively.
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Potential Game theoretic analysis of a market based decentralized task allocation algorithm
Distributed Autonomous Robotic Systems, 2016Co-Authors: Han-lim Choi, Keumseong Kim, Luke B Johnson, Jonathan P HowAbstract:This paper presents a Potential Game-theoretic interpretation and analysis of a decentralized task allocation algorithm, consensus-based bundled algorithm, which was developed by the authors’ prior work. It is, in particular, proved that the consensus-based bundle algorithm converges to a pure strategy Nash equilibrium of some distributed welfare Game, and the price of anarchy and the price of stability of this equilibrium are 1/2 and 1, respectively.
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A Potential-Game Approach for Information-Maximizing Cooperative Planning of Sensor Networks
IEEE Transactions on Control Systems Technology, 2015Co-Authors: Han-lim Choi, Su-jin LeeAbstract:This paper presents a Potential-Game approach for distributed cooperative selection of informative sensors, when the goal is to maximize the mutual information between the measurement variables and the quantities of interest. It is proved that a local utility function defined by the conditional mutual information of an agent conditioned on the other agents’ sensing decisions leads to a Potential Game, with the global Potential being the original mutual information of the cooperative planning problem. The joint strategy fictitious play method is then applied to obtain a distributed solution that provably converges to a pure strategy Nash equilibrium. Two illustrative numerical examples are presented to demonstrate good convergence and performance properties of the proposed Game-theoretic method.
