30,215 research outputs found
Power control and receiver design for energy efficiency in multipath CDMA channels with bandlimited waveforms
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
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
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
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
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
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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