30,215 research outputs found

    Power control and receiver design for energy efficiency in multipath CDMA channels with bandlimited waveforms

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    This paper is focused on the cross-layer design problem of joint multiuser detection and power control for energy-efficiency optimization in a wireless data network through a game-theoretic approach. Building on work of Meshkati, et al., wherein the tools of game-theory are used in order to achieve energy-efficiency in a simple synchronous code division multiple access system, system asynchronism, the use of bandlimited chip-pulses, and the multipath distortion induced by the wireless channel are explicitly incorporated into the analysis. Several non-cooperative games are proposed wherein users may vary their transmit power and their uplink receiver in order to maximize their utility, which is defined here as the ratio of data throughput to transmit power. In particular, the case in which a linear multiuser detector is adopted at the receiver is considered first, and then, the more challenging case in which non-linear decision feedback multiuser detectors are employed is considered. The proposed games are shown to admit a unique Nash equilibrium point, while simulation results show the effectiveness of the proposed solutions, as well as that the use of a decision-feedback multiuser receiver brings remarkable performance improvements.Comment: appeared in the Proceedings of the 41st Annual Conference on Information Sciences and Systems, John Hopkins University, March 200

    A Non-Cooperative Game Theoretical Approach For Power Control In Virtual MIMO Wireless Sensor Network

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    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 (VMIMO-WSN)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 VMIMO-WSN architecture achieves the best utility, by consuming less power.Comment: 12 pages, 8 figure

    Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches

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    An overview of game-theoretic approaches to energy-efficient resource allocation in wireless networks is presented. Focusing on multiple-access networks, it is demonstrated that game theory can be used as an effective tool to study resource allocation in wireless networks with quality-of-service (QoS) constraints. A family of non-cooperative (distributed) games is presented in which each user seeks to choose a strategy that maximizes its own utility while satisfying its QoS requirements. The utility function considered here measures the number of reliable bits that are transmitted per joule of energy consumed and, hence, is particulary suitable for energy-constrained networks. The actions available to each user in trying to maximize its own utility are at least the choice of the transmit power and, depending on the situation, the user may also be able to choose its transmission rate, modulation, packet size, multiuser receiver, multi-antenna processing algorithm, or carrier allocation strategy. The best-response strategy and Nash equilibrium for each game is presented. Using this game-theoretic framework, the effects of power control, rate control, modulation, temporal and spatial signal processing, carrier allocation strategy and delay QoS constraints on energy efficiency and network capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on Resource-Constrained Signal Processing, Communications and Networking, May 200

    A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay QoS Constraints

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    A game-theoretic framework is used to study the effect of constellation size on the energy efficiency of wireless networks for M-QAM modulation. A non-cooperative game is proposed in which each user seeks to choose its transmit power (and possibly transmit symbol rate) as well as the constellation size in order to maximize its own utility while satisfying its delay quality-of-service (QoS) constraint. The utility function used here measures the number of reliable bits transmitted per joule of energy consumed, and is particularly suitable for energy-constrained networks. The best-response strategies and Nash equilibrium solution for the proposed game are derived. It is shown that in order to maximize its utility (in bits per joule), a user must choose the lowest constellation size that can accommodate the user's delay constraint. This strategy is different from one that would maximize spectral efficiency. Using this framework, the tradeoffs among energy efficiency, delay, throughput and constellation size are also studied and quantified. In addition, the effect of trellis-coded modulation on energy efficiency is discussed.Comment: To appear in the IEEE Journal on Selected Areas in Communications (JSAC): Special Issue on Non-Cooperative Behavior in Networking, August 200

    Distributed stochastic optimization via matrix exponential learning

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    In this paper, we investigate a distributed learning scheme for a broad class of stochastic optimization problems and games that arise in signal processing and wireless communications. The proposed algorithm relies on the method of matrix exponential learning (MXL) and only requires locally computable gradient observations that are possibly imperfect and/or obsolete. To analyze it, we introduce the notion of a stable Nash equilibrium and we show that the algorithm is globally convergent to such equilibria - or locally convergent when an equilibrium is only locally stable. We also derive an explicit linear bound for the algorithm's convergence speed, which remains valid under measurement errors and uncertainty of arbitrarily high variance. To validate our theoretical analysis, we test the algorithm in realistic multi-carrier/multiple-antenna wireless scenarios where several users seek to maximize their energy efficiency. Our results show that learning allows users to attain a net increase between 100% and 500% in energy efficiency, even under very high uncertainty.Comment: 31 pages, 3 figure

    A Repeated Game Formulation of Energy-Efficient Decentralized Power Control

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    Decentralized multiple access channels where each transmitter wants to selfishly maximize his transmission energy-efficiency are considered. Transmitters are assumed to choose freely their power control policy and interact (through multiuser interference) several times. It is shown that the corresponding conflict of interest can have a predictable outcome, namely a finitely or discounted repeated game equilibrium. Remarkably, it is shown that this equilibrium is Pareto-efficient under reasonable sufficient conditions and the corresponding decentralized power control policies can be implemented under realistic information assumptions: only individual channel state information and a public signal are required to implement the equilibrium strategies. Explicit equilibrium conditions are derived in terms of minimum number of game stages or maximum discount factor. Both analytical and simulation results are provided to compare the performance of the proposed power control policies with those already existing and exploiting the same information assumptions namely, those derived for the one-shot and Stackelberg games.Comment: 25 pages, 5 figures, accepted for publication in IEEE Transaction on Wireless Communicatio
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