Results 11  20
of
74
A noncooperative power control game for multicarrier CDMA systems
 In Proc. IEEE Wireless Communications and Networking Conference (WCNC
, 2005
"... A gametheoretic model for studying power control in multicarrier CDMA systems is proposed. Power control is modeled as a noncooperative game in which each user must decide how much power to transmit over each carrier to maximize its own utility. The utility function considered here measures the n ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
(Show Context)
A gametheoretic model for studying power control in multicarrier CDMA systems is proposed. Power control is modeled as a noncooperative game in which each user must decide how much power to transmit over each carrier to maximize its own utility. The utility function considered here measures the number of reliable bits transmitted over all the carriers per joule of energy consumed and is particularly suitable for networks where energy efficiency is important. The multidimensional nature of users ’ strategies and nonquasiconcavity of the utility function make the multicarrier problem much more challenging than the singlecarrier case. It is shown that, for all linear receivers including the matched filter, decorrelating and minimum mean square error (MMSE) detectors, a user’s utility is maximized when the user transmits only on its “best ” carrier. This is the carrier that requires the least amount of power to achieve a particular target signal to interference plus noise ratio (SIR) at the output of the receiver. The existence and uniqueness of Nash equilibrium for the proposed power control game are studied. In particular, we give conditions that must be satisfied by the channel gains for a Nash equilibrium to exist and also characterize the distribution of the users among the carriers at equilibrium. In addition, an iterative and distributed algorithm for reaching the equilibrium (when it exists) is presented. It is shown that the proposed approach results in a significant improvement in the total utility achieved at equilibrium compared to the case in which each user maximizes its utility over each carrier independently.
A NONCOOPERATIVE GAME THEORETICAL APPROACH FOR POWER CONTROL IN VIRTUAL MIMO WIRELESS SENSOR NETWORK
"... Power management is one of the vital issue in wireless sensor networks, where the lifetime of the network relies on battery powered nodes. Transmitting at high power reduces the lifetime of both the nodes and the network. One efficient way of power management is to control the power at which the nod ..."
Abstract

Cited by 7 (1 self)
 Add to MetaCart
(Show Context)
Power management is one of the vital issue in wireless sensor networks, where the lifetime of the network relies on battery powered nodes. Transmitting at high power reduces the lifetime of both the nodes and the network. One efficient way of power management is to control the power at which the nodes transmit. In this paper, a virtual multiple input multiple output wireless sensor network (VMIMOWSN) communication architecture is considered and the power control of sensor nodes based on the approach of game theory is formulated. The use of game theory has proliferated, with a broad range of applications in wireless sensor networking. Approaches from game theory can be used to optimize node level as well as network wide performance. The game here is categorized as an incomplete information game, in which the nodes do not have complete information about the strategies taken by other nodes. For virtual multiple input multiple output wireless sensor network architecture considered, the Nash equilibrium is used to decide the optimal power level at which a node needs to transmit, to maximize its utility. Outcome shows that the game theoretic approach considered for VMIMOWSN architecture achieves the best utility, by consuming less power.
Optimal Power Control for Cognitive Radio Networks Under Coupled Interference Constraints: A Cooperative GameTheoretic Perspective
"... Abstract—Distributed power control is investigated for cognitive radio networks (CRNs) based on a cooperative gametheoretic framework. Taking into consideration both network efficiency and user fairness, a cooperative Nash bargaining powercontrol game (NBPCG) model is formulated, where interference ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
Abstract—Distributed power control is investigated for cognitive radio networks (CRNs) based on a cooperative gametheoretic framework. Taking into consideration both network efficiency and user fairness, a cooperative Nash bargaining powercontrol game (NBPCG) model is formulated, where interference power constraints (IPCs) are imposed to protect the primary users ’ (PUs’) transmissions, and minimum signaltointerferenceplusnoise ratio (SINR) requirements are employed to provide reliable transmission opportunities to secondary cognitive users. An SINRbased utility function is designed for this game model, which not only reflects the spectrum efficiency of the CRN but also complies with all the axioms in the Nash theorem and, hence, facilitates efficient algorithmic development. The existence, uniqueness, and fairness of this game solution are proved analytically. To deal with the IPCs where the powercontrol decisions of all users are coupled, these IPCs are properly transformed into a pricing function in the objective utility. Accordingly, a Kalai–Smorodinsky (KS) bargaining solution and a Nash bargaining solution (NBS) are developed, which result in Paretooptimal solutions to the NBPCG problem with different userfairness policies. Theoretical analysis and simulations are provided to testify the effectiveness of the proposed cooperative game algorithms for efficient and fair power control in CRNs. Index Terms—Cognitive radio networks (CRNs), cooperative game theory, fairness, Kalai–Smorodinsky (KS) bargaining game, Nash bargaining game, power control. I.
Statistical learning theory to evaluate the performance of game theoretic power control algorithms for wireless data in arbitrary channels
 in Proc. IEEE Wireless Commun. and Networking Conf
, 2003
"... Abstract—In this paper we use statistical learning theory to evaluate the performance of game theoretic power control algorithms for wireless data in arbitrary channels, i.e., no presumed channel model is required. To show the validity of statistical learning theory in this context, we studied a fla ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
(Show Context)
Abstract—In this paper we use statistical learning theory to evaluate the performance of game theoretic power control algorithms for wireless data in arbitrary channels, i.e., no presumed channel model is required. To show the validity of statistical learning theory in this context, we studied a flat fading channel, and more specifically, we simulated the case of Rayleigh flat fading channel. With the help of a relatively small number of training samples, the results suggest the learnability of the utility function classes defined by changing the users power (adjusted parameter) for each user’s utility function. I.
SIRBASED POWER CONTROL IN 3G WIRELESS CDMA NETWORKS
, 2003
"... For one year from the date of this document, distribution limited to WINLAB ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
(Show Context)
For one year from the date of this document, distribution limited to WINLAB
A Distributed PowerAllocation and SignalShaping Game for the Competitively Optimal ThroughputMaximization of MultipleAntenna “ad hoc” Networks
, 2006
"... This paper focuses on the competitively optimal power control and signal shaping for “ad hoc” networks composed by multipleantenna noncooperative transmit/receive terminals affected by spatially colored multipleaccess interference (MAI). The target is the competitive maximization of the informati ..."
Abstract

Cited by 3 (1 self)
 Add to MetaCart
This paper focuses on the competitively optimal power control and signal shaping for “ad hoc” networks composed by multipleantenna noncooperative transmit/receive terminals affected by spatially colored multipleaccess interference (MAI). The target is the competitive maximization of the information throughput sustained by each link that is active over the network. For this purpose, the MAIimpaired network is modeled as a noncooperative strategic game, and sufficient conditions for the existence and uniqueness of the Nash equilibrium (NE) are provided. Furthermore, iterative powercontrol and signalshaping algorithms are presented to efficiently achieve the NE under both besteffort and “contracted QoS ” policies. The presented algorithms also account for the effect of (possibly) imperfect channel estimates available at the transmit/receive units active over the network, they are fully scalable, and they may be implemented in a fully distributed
A Gametheoretic Analysis of Link Adaptation in Cellular Radio Networks
, 2004
"... In recent years, game theory has emerged as a promising approach to solving the power control problem in wireless networks. This thesis extends the reach of gametheoretic analysis to embrace link adaptation, thereby constituting a generalization of the power control problem. A realistic and natural ..."
Abstract

Cited by 3 (1 self)
 Add to MetaCart
(Show Context)
In recent years, game theory has emerged as a promising approach to solving the power control problem in wireless networks. This thesis extends the reach of gametheoretic analysis to embrace link adaptation, thereby constituting a generalization of the power control problem. A realistic and natural problem formulation is attempted, wherein transmitter power and a discretevalued Adaptable Link Parameter (ALP), e.g. code rate, constitute the action set of a player in this game. The dual goals of maximizing throughput and minimizing power consumption are reflected in the utility function selection, which uses the accurate sigmoid model for approximating throughput. The discrete action space makes it difficult to verify the existence of a Nash Equilibrium (NE) in this game using standard techniques. To circumvent this limitation, a heuristic algorithm is proposed. This algorithm is analytically shown to always converge to a NE. The subsequent results probe its validity and sensitivity. Favorable comparisons are drawn between these gametheoretic results and those arising from parallel systems techniques. A linear programming system optimization that exploits properties of the
MultiAntenna Cognitive Radio for Broadband . . .
, 2007
"... This paper focuses on the competitively optimal powercontrol, signalshaping and interference mitigation for wireless mesh networks composed by MultipleAntenna noncooperative transmit terminals and a base station affected by spatially colored MultiAccess Interference (MAI). The target is the comp ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
This paper focuses on the competitively optimal powercontrol, signalshaping and interference mitigation for wireless mesh networks composed by MultipleAntenna noncooperative transmit terminals and a base station affected by spatially colored MultiAccess Interference (MAI). The target is the competitive maximization of the information throughput of the uplink of each link active over the network. For this purpose, the MAIimpaired network is modelled as a noncooperative strategic game. Specifically, the main contribution of this paper may be so summarized. First, we consider powercontrol, signalshaping and interference mitigation algorithms allowing the implementation of asynchronous SpaceDivision Multiple Access (SDMA) strategies able to guarantee the competitive maximization of the users ’ rate under both Quality of Service (QoS) guaranteed and QoS contracted access policies. Second, we give evidence that the developed SDMA outperforms (in terms of aggregate throughput) the conventional orthogonal ones, specially in operating scenarios affected by strong MAI. The proposed access scheme can be considered as an Active Networking strategy where the nodes try to ”sense” the channel and to access according to a spacedivision policy.
A game theoretic approach for power aware middleware
 in Middleware ’04: Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
, 2004
"... Abstract. In this paper, we propose a dynamic game theoretic approach for choosing power optimization strategies for various components(e.g. cpu, network interface etc.) of a lowpower device operating in a distributed environment. Specifically, we model the energy consumption problem as a dynamic ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
Abstract. In this paper, we propose a dynamic game theoretic approach for choosing power optimization strategies for various components(e.g. cpu, network interface etc.) of a lowpower device operating in a distributed environment. Specifically, we model the energy consumption problem as a dynamic noncooperative game theoretic problem, where the various components of the device are modelled as the players in the game that simultaneously consume a common resource(device battery power). An analysis for the Nash and social optima of the game is presented. We then introduce an adaptive distributed poweraware middleware framework, called "Dynamo", that incorporates the game theoretic approach for determining optimal power optimization strategies. We simulate the distributed game environment for proxybased video streaming to a mobile handheld device. Our performance results indicate that significant energy savings are achievable for the device when the energy usage of the individual components achieve a social optima than when the energy usage achieves the strategic Nash equilibria. The overall utility of the system is measured both in terms of energy gains and the quality of video playback. Our results indicate that the device lifetime was increased by almost 50%90% when compared to the case where no power optimization strategies were used, and 3040% over device lifetime when Nash equilibrium is achieved; the overall utility of system for both types of equilibria were similar(utilities differ by ≤ .5%), indicating that the Nash equilibrium strategies tend to overuse the battery energy consumption. 1 Key words: power optimization, game theory, poweraware middleware Motivation Limiting the energy consumption of lowpower mobile devices has become an important research objective in recent years. The capabilities of these devices are limited by their modest sizes and the finite lifetimes of the batteries that power them. As a result, minimizing the energy usage of every component (e.g. CPU, network card, display, architecture etc.) in such devices remains an important design goal and continues to pose significant challenges. These issues have been aggressively pursued by researchers and numerous interesting power optimization solutions have been proposed at various cross computational levels system cache and external memory access optimizations