26,383 research outputs found
A Non-Cooperative Power Control Game in Delay-Constrained Multiple-Access Networks
A game-theoretic approach for studying power control in multiple-access
networks with transmission delay constraints is proposed. A non-cooperative
power control game is considered in which each user seeks to choose a transmit
power that maximizes its own utility while satisfying the user's delay
requirements. The utility function measures the number of reliable bits
transmitted per joule of energy and the user's delay constraint is modeled as
an upper bound on the delay outage probability. The Nash equilibrium for the
proposed game is derived, and its existence and uniqueness are proved. Using a
large-system analysis, explicit expressions for the utilities achieved at
equilibrium are obtained for the matched filter, decorrelating and minimum mean
square error multiuser detectors. The effects of delay constraints on the
users' utilities (in bits/Joule) and network capacity (i.e., the maximum number
of users that can be supported) are quantified.Comment: To apprear in the proceedings of the 2005 IEEE International
Symposium on Information Theory, Adelaide, Australia, September 4-9, 200
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
Energy-Efficient Resource Allocation in Wireless Networks with Quality-of-Service Constraints
A game-theoretic model is proposed to study the cross-layer problem of joint
power and rate control with quality of service (QoS) constraints in
multiple-access networks. In the proposed game, each user seeks to choose its
transmit power and rate in a distributed manner in order to maximize its own
utility while satisfying its QoS requirements. The user's QoS constraints are
specified in terms of the average source rate and an upper bound on the average
delay where the delay includes both transmission and queuing delays. The
utility function considered here measures energy efficiency and is particularly
suitable for wireless networks with energy constraints. The Nash equilibrium
solution for the proposed non-cooperative game is derived and a closed-form
expression for the utility achieved at equilibrium is obtained. It is shown
that the QoS requirements of a user translate into a "size" for the user which
is an indication of the amount of network resources consumed by the user. Using
this competitive multiuser framework, the tradeoffs among throughput, delay,
network capacity and energy efficiency are studied. In addition, analytical
expressions are given for users' delay profiles and the delay performance of
the users at Nash equilibrium is quantified.Comment: Accpeted for publication in the IEEE Transactions on Communication
A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay 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. Using this framework, the tradeoffs among energy efficiency, delay,
throughput and constellation size are also studied and quantified. The effect
of trellis-coded modulation on energy efficiency is also discussed.Comment: Appeared in the Proceedings of the 2007 IEEE Radio and Wireless
Symposium, Long Beach, CA, January 9-11, 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
Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks
The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm
which incorporates the cloud computing into heterogeneous networks (HetNets),
thereby taking full advantage of cloud radio access networks (C-RANs) and
HetNets. Characterizing the cooperative beamforming with fronthaul capacity and
queue stability constraints is critical for multimedia applications to
improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization
objective function with individual fronthaul capacity and inter-tier
interference constraints is presented in this paper for queue-aware multimedia
H-CRANs. To solve this non-convex objective function, a stochastic optimization
problem is reformulated by introducing the general Lyapunov optimization
framework. Under the Lyapunov framework, this optimization problem is
equivalent to an optimal network-wide cooperative beamformer design algorithm
with instantaneous power, average power and inter-tier interference
constraints, which can be regarded as the weighted sum EE maximization problem
and solved by a generalized weighted minimum mean square error approach. The
mathematical analysis and simulation results demonstrate that a tradeoff
between EE and queuing delay can be achieved, and this tradeoff strictly
depends on the fronthaul constraint
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
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