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2009
The ability to model individual, independent decision makers whose actions potentially affect all other decision makers renders game theory particularly attractive to apply to various fields of Information technology, especially, to analyze the performance of wireless networks. In this paper, we discuss how various interactions in cognitive radio based wireless networks can be modeled as a game at different levels of protocol stack. This allows the analysis of existing protocols and resource management schemes, as well as the design of equilibrium-inducing mechanisms that provide incentives for individual users to behave in socially-constructive ways. In nutshell, this paper serves two main objectives; first, to model some of the fundamental questions on cognitive radio based wireless networks as interactive games between the nodes and second, to gain our understanding on inter-discipline research issues.
2012 10th International Conference on Frontiers of Information Technology, 2012
Development of a system in which several unlicensed users strive to access the vacant licensed bands is a highly challenging task, especially in ad hoc networks where no centralized infrastructure exists. These unlicensed users, also called cognitive radios, must compete for the available frequency slots. The convergence of this system is difficult to achieve if nodes perform no information exchange and solely depend on their individual actions. In this paper, we analyze the cognitive radio networks for distributed channel allocation. It is observed that convergence is easier to establish in cooperative systems or systems where users perform information exchange. This kind of cooperative behavior can be enforced by providing incentives to nodes. The cooperation leads to an improvement in overall network performance as compared to the selfish users who are concerned only with their individual benefits.
2014 IEEE Military Communications Conference, 2014
Current coexistence protocols employed for contention by collocated Cognitive Radio Networks (CRN), such as the IEEE 802.22 WRAN, assume that the contending networks do not have any preference over the set of available channels. Having channels with different quality parameters can lead to an imbalance in contention for disparate channels, degraded quality of service and an overall inefficient utilization of spectrum resources. In this paper, we analyze this situation from a game theoretic perspective and model coexistence of CRNs as a noncooperative, repeated general-sum game with perfect information. We demonstrate that due to the possibility of its centralized as well as a distributed implementation, the correlated equilibrium is a practical solution for the problems of inefficiency and unfairness of Nash Equilibria. It not only induces voluntary cooperation among non-cooperative CRNs and results in optimum spectrum utilization but also results in an egalitarian equilibrium which maximizes the minimum payoff for every CRN.
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.
Game theory is a set of tools developed to model interactions between agents with conflicting interests . It is a field of applied mathematics that defines and evaluates interactive decision situations. It provides analytical tools to predict the outcome of complicated interactions between rational entities, where rationality demands strict adherence to a strategy based on observed or measured results . Originally developed to model problems in the field of economics, game theory has recently been applied to network problems, in most cases to solve the resource allocation problems in a competitive environment. The reason that game theory is an adapted choice for studying cooperative communications is various. Nodes in the network are independent agents, making decisions only for their own interests. Game theory provides us sufficient theoretical tools to analyze the network users' behaviors and actions. Game theory, also primarily deals with distributed optimization, which often requires local information only. Thus it enables us to design distributed algorithms. . This article surveys the literature on game theory as they apply to wireless networks. First, a brief overview of classifications of games, important definitions used in games (Nash Equilibrium, Pareto efficiency, Pure, Mixed and Fully mixed strategies) and game models are presented. Then, we identified five areas of application of game theory in wireless networks; therefore, we discuss related work to game theory in communication networks, cognitive radio networks, wireless sensor networks, resource allocation and power control. Finally, we discuss the limitations of the application of game theory in wireless networks.
2015
Optimal resource management in a cognitive radio network has been studied using the game theory. Based on personal interests, users select their own desired utility function and compete for channel and power selection. This non-cooperative approach is controlled through an appropriate pricing method. We have shown that if the utility function in a cooperative potential game is used as the pricing function in a non-cooperative network, the game governing the non-cooperative network will also become potential and will thus converge to Nash equilibrium. The existence of selfish users will cause the network to be unstable, the one which has presumptively been designed with users’ cooperation. Besides, it decreases resource utilization gain. Using the recommended pricing has been shown to equilibrate the network. The equilibrium points also enjoy some optimality criteria such as Pareto optimality. By conducting simulations and studying parameters like sum-rate of network and its total interference, it is shown that resource utilization will also approaches to optimal states.
IEEE Signal Processing Magazine, 2000
Under certain assumptions in terms of information and models, equilibria correspond to possible stable outcomes in conflicting or cooperative scenarios where rational entities interact. For wireless engineers, it is of paramount importance to be able to predict and even ensure such states at which the network will effectively operate. In this article, we provide non-exhaustive methodologies for characterizing equilibria in wireless games in terms of existence, uniqueness, selection, and efficiency. June 2, 2009 DRAFT 2 for communications and especially wireless communications have been released over the past fifteen years ([5], [6], [7], [8], [9]
2009
Cognitive Radio Networks aim at enhancing spectrum utilization by allowing cognitive devices to opportunistically access vast portions of the spectrum. To reach such ambitious goal, cognitive terminals must be geared with enhanced spectrum management capabilities including the detection of unused spectrum holes (spectrum sensing), the characterization of available bands (spectrum decision), the coordination with other cognitive devices in the access phase (spectrum sharing), and the capability to handover towards other spectrum holes when licensed users kick in or if a better spectrum opportunity becomes available (spectrum mobility).
2008 IEEE International Conference on Communications, 2008
In this paper we develop a framework for resource allocation in a secondary spectrum access scenario where a group of Cognitive Radios (CR) access the resources of a primary system. We assume the primary system is a cellular OFDM-based network. We develop the optimum resource allocation strategies which guarantee a level of QoS, defined by minimum rate and the target Bit Error Rate (BER), for the primary system. Using the Game theoretic axiom of fairness, i.e., Nash Bargaining Solutions (NBS), we show that by allocating a priority factor to all players an efficient and fair resource allocation can be achieved. We show how the priority factors are assigned in this scheme and outline a method to select the users who are allowed to share a specific sub-channel.
This paper presents a powerful innovative multi-layer game theoretical modelling framework for the evolution of spectrum markets. It integrates models of the channel, client and network operator (provider) paradigms, wireless infrastructures, types of interaction, and price adaptation. This modelling framework incorporates an extensive set of parameters that allow the modelling of various complex interactions of CRNs entities and business-driven cases in multiple spatio-temporal scales in a realistic manner. It also provides a modular simulation environment that implements this framework to enable researchers to instantiate various models and perform comparative assessments of spectrum-sharing and spectrum-provision mechanisms. To address several practical and systems-based issues, we proposed two novel mechanisms: a price adaptation algorithm for providers and the u-map, a user-centric community-based mechanism that enables clients to record and upload their feedback about their QoE during a call in a shared location-based database. To illustrate how the proposed modelling framework and simulation platform can be used, this paper analyzes the evolution of a cellular-based market that uses the proposed price adaptation algorithm. In the context of this market, we also evaluated the u-map and show how it can improve the network operator selection process. Finally, we discuss how this framework and simulation platform can be extended to analyze various spectrum markets and cognitive radio networks (CRNs).
2012 IEEE Globecom Workshops, 2012
The dynamic behavior for spectrum management in cognitive radio networks is considered in this paper, which consists of spectrum trading and spectrum competition among multiple spectrum owners and spectrum leasers. The primary users adjust their behaviors in renting the spectrum to secondary users in order to achieve higher profits. The secondary users adjust the spectrum renting by observing the changes in the price and the quality of the spectrum. It is however problematic when the primary users and secondary users make the decisions dynamically. A three layer game theoretic approach is introduced in this paper to address this problem. The upper layer models the spectrum competition among primary users; a Bertrand game is formulated where the Nash equilibrium is considered as the solution. The middle layer models the spectrum trading between the primary user and secondary user; a Stackelberg game is formulated where the Nash equilibrium is considered as the solution. The lower layer models the dynamic selection strategies among secondary users in order to select the offered spectrum; an evolutionary game is formulated where the Nash equilibrium is the solution. Basically, the solution in each game is found in terms of the size of the offered spectrum to the secondary users and the spectrum price. The proposed game theory model is used to examine network dynamics under different levels of QoS where the actions of each user are made dynamically.
2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2014
This paper develops policies for channel allocation in Cognitive Radio Networks (CRN). Game Theory is a tool which can be applied to allocate the limited resources among the selfish users in CRN. The distributed users actions and decisions can drive the system into an equilibrium state. We analyze the Nash Equilibrium (NE) solution for different CRN scenarios beginning from simple scenarios ('Fixed: 3 link, 2 ch' and 'Fixed and Random: 5 link, 3 ch') then to a more complex one ('Random: 10 link, 4 ch'). We then develop policies for channel allocation for CRN based on the results obtained. These general policies can be used in other CRN scenarios to reach equilibrium solutions with less computation resources and time. Index Terms-Cognitive Radio Network (CRN), Nash Equilibrium (NE), Channel allocation policies.
International Journal of Students’ Research in Technology & Management, 2017
Cognitive Radio (CR) technology is imagined to solve the problems in Wireless Ad-hoc NETworks (WANET) resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. Game theory is a process to analyze multi-person decision making situation, where each decision maker tries to maximize his own utility. In this paper, we illustrates how various interactions in Cognitive Radio Ad Hoc Network (CRAHN) can be modeled as a game. It also illustrates a problem with solution approach that uses intelligent game theory technique in CRAHN.
2011
With increasing demand for data transfer requirements on wireless networks, spectrum became a scarce resource due to inefficient allocation and management. Recent research efforts diverted the problem towards dynamic spectrum access models for effective utilization of the unused or idled spectrum. The models include overlay/underlay techniques by designing the framework to improve the spectrum efficiently by using business and game theory models. Surveying of these models concludes that the key component for efficient utilization of the unused spectrum is the detection of the unused spectrum at any given time. Further, we found that by allocating the unused spectrum using appropriate techniques (business, game, and hybrid models) will produce better results. Among these models, the game models were identified as one of the powerful mathematical tools to detect and allocate the unused spectrum. In this paper, we first discussed the role of game models in wireless communications, player"s strategy selection for better utility, and then proposed a correlated equilibrium algorithm for efficient allocation of spectrum. The simulations conclude that the mixed strategies are better than the pure strategies in resource allocation.
2013
In wireless communication networks, many protocols (e.g., IEEE 802.11 a/b/g Medium Access Control (MAC) protocols) have been designed assuming that users are compliant with the protocol rules. Unfortunately, a self-interested and strategic user might manipulate the protocol to obtain a personal advantage at the expense of the other users. This would lead to socially inefficient outcomes. In this thesis we address the problem of designing protocols that are able to avoid or limit the inefficiencies occurring when the users act selfishly and strategically. To do so, we exploit the tools offered by Game Theory (GT), the branch of mathematics that models and analyzes the interaction between strategic decision makers. The dissertation covers aspects related to wireless communications at different levels. We start analyzing the downlink radio resource allocation issue of a cellular network based on Orthogonal Frequency Division Multiple Access (OFDMA). We propose a suboptimal game theoretic algorithm able to preserve the modularity of the system and to trade-off between sum-rate throughput and fairness among the users of the network. Successively, we address the problem of promoting cooperation in wireless relay networks. To give the incentive for the users of a network to relay the packets sent by other users, we consider a dynamic scheduling in which cooperative users are rewarded with more channel access opportunities. Infrastructure sharing is another form of cooperation that might be exploit to meet the increasing rate demands and quality of service requirements in wireless networks. We analyze a scenario where two wireless multi-hop networks are willing to share some of their nodes-acting as relays-in order to gain benefits in terms of lower packet delivery delay and reduced loss probability. Bayesian Network analysis is exploited to compute the correlation between local parameters and overall performance, whereas the selection of the nodes to share is made by means of a game theoretic approach. Afterwards, our analysis focuses on channel access policies in wireless ad-hoc networks. We design schemes based on pricing and intervention to give incentives for the users to access the channel efficiently.
IEEE Communications Surveys & Tutorials, 2005
The application of mathematical analysis to the study of wireless ad hoc networks has met with limited success due to the complexity of mobility and traffic models, the dynamic topology, and the unpredictability of link quality that characterize such networks. The ability to model individual, independent decision makers whose actions potentially affect all other decision makers renders game theory particularly attractive to analyze the performance of ad hoc networks. In this paper, we describe how various interactions in wireless ad hoc networks can be modeled as a game. This allows the analysis of existing protocols and resource management schemes, as well as the design of equilibrium-inducing mechanisms that provide incentives for individual users to behave in socially-constructive ways. We survey the recent literature on game theoretic analysis of ad hoc networks, highlighting its applicability to power control and waveform adaptation, medium access control, routing, and node participation, among others.
Journal of Communications, 2009
The ability to model independent decision makers whose actions potentially affect all other decision makers makes game theory attractive to analyze the performances of wireless communication systems. Recently, there has been growing interest in adopting game theoretic methods to cognitive radio networks for power control, rate adaptation and channel access schemes. This work presents several results in game theory and their applications in cognitive radio systems. First, we compute the Nash equilibrium power allocation and rate adaptation policies in cognitive radio systems using static game and dynamic Markovian game frameworks. We then describe how mechanism design helps to design a truth revealing channel access scheme. Finally, we introduce the correlated equilibrium concept in stochastic games and its application to solve the transmission control problem in a cognitive radio system.
International Journal of Computer Applications, 2014
In this paper, resource allocation models for cognitive radio networks (CRN) using game theory are presented. The study includes the concept of cognitive radio (CR) networks, cooperative and non-cooperative game theory, and modeling of strategic interaction process for CR enabled secondary users. The prime objective of the present study is to compare existing game models for CR networks in terms of concept, approach, system model, and issues associated with each model. At last, conclusion for implementing game models in the cognitive radio networks for effective management of available radio resources is given to provide direction to researchers for future work.
In this paper, cooperative communications are presented to improve efficiency toward the use of telecommunication systems resources. In the special case of cognitive radio networks, main benefits and costs regarding cooperation are analyzed, as well as security issues that might rise in such a scenario. From a game theory model, the implementation of a coalitional game is described, where cognitive users pursue individual benefits as well as benefits for the coalition they belong. Simulation results confirm the gains achievable by means of cooperative communications, and reveal weakening performance in presence of security threats. This paper may help readers to have a more comprehensive understanding of cooperative communications based on game theory, as well as the main research trends and challenges in this area.
European Transactions on Telecommunications, 2011
We present a framework and pertinent formulations for a coalition of secondary cognitive radios that are willing to lease inactive spectrum band from a primary system through auctioning and to share the received bandwidth and the associated cost among themselves using multiple access techniques. We cast this scenario to submodular class of games and show how a link can be established between the truthful auctioning mechanism and the cost-sharing algorithm. Simulation results verify that the deployed cost-sharing technique leads to encouraging the secondary cognitive radios to truthfully announce their bids.
"Efficient resource allocation is one of the key concerns of implementing cognitive radio networks. Game theory has been extensively used to study the strategic interactions between primary and secondary users for effective resource allocation. The concept of spectrum trading has introduced a new direction for the coexistence of primary and secondary users through economic benefits to primary users. The use of price theory and market theory from economics has played a vital role to facilitate economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks. With this motivation, we present an extensive summary of the related work that use economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks."
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