Results 1  10
of
314
Efficient power control via pricing in wireless data networks
 IEEE Transactions on Communication
, 2000
"... A major challenge in operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With increasing demand for wireless data servic ..."
Abstract

Cited by 201 (6 self)
 Add to MetaCart
A major challenge in operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With increasing demand for wireless data services, it is necessary to establish power control algorithms for information sources other than voice. We present a power control solution for wireless data in the analytical setting of a game theoretic framework. In this context, the quality of service (QoS) a wireless terminal receives is referred to as the utility and distributed power control is a noncooperative power control game where users maximize their utility. The outcome of the game results in a Nash equilibrium that is ine#cient. We introduce pricing of transmit powers in order to obtain Pareto improvement of the noncooperative power control game, i.e. to obtain improvements in user utilities relative to the case with no pricing. Specifically, we consider a pricing function that is a linear function of the transmit power. The simplicity of the pricing function allows a distributed implementation where the price can be broadcast by the base station to all the terminals. We see that pricing is especially helpful in a heavily loaded system.
Joint Scheduling and Power Control for Wireless Adhoc Networks
, 2002
"... In this pape we introduce powe r control as a solution tothe multiple accel proble in conte tionbase wirenb adhocne works.The motivation for this study is two fold, limiting multiuse intej toincre single hop throughput, andrej powe r consumption to increj batte life We focus onne ne bor transmi ..."
Abstract

Cited by 189 (5 self)
 Add to MetaCart
In this pape we introduce powe r control as a solution tothe multiple accel proble in conte tionbase wirenb adhocne works.The motivation for this study is two fold, limiting multiuse intej toincre single hop throughput, andrej powe r consumption to increj batte life We focus onne ne bor transmissions whes node are rej tose information packe  tothe re e e re e sub jej to a constraint on the signaltointealtoinjj ratio.The multiple acce  proble is solve via twoaltej phase name schej and powe r control.The sche algorithm isej tial to coordinate the transmissions ofinde ede t use inorde toejj strong intej (e.g selfinterference) that can not be ove by powe r control. On the othe hand, powe r control isej in adistribute fashion to dej the admissible powe r ve ifone ene that can be use bythe sche use to satisfy thei singlej transmissionrensmissi ts. This isdone for two type s ofne works, namej TDMA and TDMA/CDMA wire/CD adhocne works.
Multiaccess Fading Channels  Part I: Polymatroid Structure, Optimal Resource Allocation and Throughput Capacities
 IEEE Trans. Inform. Theory
"... In multiaccess wireless systems, dynamic allocation of resources such as transmit power, bandwidths, and rates is an important means to deal with the timevarying nature of the environment. In this twopart paper, we consider the problem of optimal resource allocation from an informationtheoretic p ..."
Abstract

Cited by 174 (9 self)
 Add to MetaCart
In multiaccess wireless systems, dynamic allocation of resources such as transmit power, bandwidths, and rates is an important means to deal with the timevarying nature of the environment. In this twopart paper, we consider the problem of optimal resource allocation from an informationtheoretic point of view. We focus on the multiaccess fading channel with Gaussian noise, and define two notions of capacity depending on whether the traffic is delaysensitive or not. In part I, we characterize the throughput capacity region which contains the longterm achievable rates through the timevarying channel. We show that each point on the boundary of the region can be achieved by successive decoding. Moreover, the optimal rate and power allocations in each fading state can be explicitly obtained in a greedy manner. The solution can be viewed as the generalization of the waterfilling construction for singleuser channels to multiaccess channels with arbitrary number of users, and exploits the underlying polymatroid structure of the capacity region. In part II, we characterize a delaylimited capacity region and obtain analogous results.
Distributed Multiuser Power Control for Digital Subscriber Lines
, 2002
"... This paper considers the multiuser power control problem in a frequencyselective interference channel. The interference channel is modeled as a noncooperative game, and the existence and uniqueness of a Nash equilibrium are established for a twoplayer version of the game. An iterative waterfillin ..."
Abstract

Cited by 170 (22 self)
 Add to MetaCart
This paper considers the multiuser power control problem in a frequencyselective interference channel. The interference channel is modeled as a noncooperative game, and the existence and uniqueness of a Nash equilibrium are established for a twoplayer version of the game. An iterative waterfilling algorithm is proposed to efficiently reach the Nash equilibrium. The iterative waterfilling algorithm can be implemented distributively without the need for centralized control. It implicitly takes into account the loop transfer functions and cross couplings, and it reaches a competitively optimal power allocation by offering an opportunity for loops to negotiate the best use of power and frequency with each other. When applied to the upstream power backoff problem in veryhigh bitrate digital subscriber lines and the downstream spectral compatibility problem in asymmetric digital subscriber lines, the new power control algorithm is found to give a significant performance improvement when compared with existing methods.
Power Control for Wireless Data
 IEEE Personal Communications
, 2000
"... Abstract With cellular phones massmarket consumer items, the next frontier is mobile multimedia communications. This situation raises the question of how to do power control for information sources other than voice. To explore this issue, we use the concepts and mathematics of microeconomics and g ..."
Abstract

Cited by 119 (12 self)
 Add to MetaCart
Abstract With cellular phones massmarket consumer items, the next frontier is mobile multimedia communications. This situation raises the question of how to do power control for information sources other than voice. To explore this issue, we use the concepts and mathematics of microeconomics and game theory. In this context, the Quality of Service of a telephone call is referred to as the "utility " and the distributed power control problem for a CDMA telephone is a "noncooperative game". The power control algorithm corresponds to a strategy that has a locally optimum operating point referred to as a "Nash equilibrium. " The telephone power control algorithm is also "Pareto efficient, " in the terminology of game theory. When we apply the same approach to power control in
CDMA Uplink Power Control as a Noncooperative Game
, 2002
"... We present a gametheoretic treatment of distributed power control in CDMA wireless systems. ..."
Abstract

Cited by 115 (22 self)
 Add to MetaCart
We present a gametheoretic treatment of distributed power control in CDMA wireless systems.
Resource allocation and crosslayer control in wireless networks
 Foundations and Trends in Networking
, 2006
"... Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner ..."
Abstract

Cited by 111 (25 self)
 Add to MetaCart
Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner in order to support information transfer. In this text we will present abstract models that capture the crosslayer interaction from the physical to transport layer in wireless network architectures including cellular, adhoc and sensor networks as well as hybrid wirelesswireline. The model allows for arbitrary network topologies as well as traffic forwarding modes, including datagrams and virtual circuits. Furthermore the time varying nature of a wireless network, due either to fading channels or to changing connectivity due to mobility, is adequately captured in our model to allow for state dependent network control policies. Quantitative performance measures that capture the quality of service requirements in these systems depending on the supported applications are discussed, including throughput maximization, energy consumption minimization, rate utility function maximization as well as general performance functionals. Crosslayer control algorithms with optimal or suboptimal performance with respect to the above measures are presented and analyzed. A detailed exposition of the related analysis and design techniques is provided. 1
Stochastic Power Control for Cellular Radio Systems
 IEEE Trans. Commun
, 1997
"... For wireless communication systems, iterative power control algorithms have been proposed to minimize transmitter powers while maintaining reliable communication between mobiles and base stations. To derive deterministic convergence results, these algorithms require perfect measurements of one or mo ..."
Abstract

Cited by 89 (8 self)
 Add to MetaCart
For wireless communication systems, iterative power control algorithms have been proposed to minimize transmitter powers while maintaining reliable communication between mobiles and base stations. To derive deterministic convergence results, these algorithms require perfect measurements of one or more of the following parameters: (i) the mobile's signal to interference ratio (SIR) at the receiver, (ii) the interference experienced by the mobile, and (iii) the bit error rate. However, these quantities are often difficult to measure and deterministic convergence results neglect the effect of stochastic measurements. In this work, we develop distributed iterative power control algorithms that use readily available measurements. Two classes of power control algorithms are proposed. Since the measurements are random, the proposed algorithms evolve stochastically and we define the convergence in terms of the mean squared error (MSE) of the power vector from the optimal power vector that is t...
Joint optimal power control and beamforming for wireless networks with antenna arrays
 in Proc. IEEE Global Telecommunications Conf. (GLOBECOM’96
, 1996
"... Abstract — The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to increase the capacity in wireless communication networks. The minimum variance distortionless response beamformer maximizes the signaltointerferenceandn ..."
Abstract

Cited by 87 (20 self)
 Add to MetaCart
Abstract — The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to increase the capacity in wireless communication networks. The minimum variance distortionless response beamformer maximizes the signaltointerferenceandnoise ratio (SINR) when it is employed in the receiver of a wireless link. In a system with omnidirectional antennas, power control algorithms are used to maximize SINR as well. In this paper, we consider a system with beamforming capabilities in the receiver, and power control. An iterative algorithm is proposed to jointly update the transmission powers and the beamformer weights so that it converges to the jointly optimal beamforming and transmission power vector. The algorithm is distributed and uses only local interference measurements. In an uplink transmission scenario, it is shown how base assignment can be incorporated in addition to beamforming and power control, such that a globally optimum solution is obtained. The network capacity and the saving in mobile power are evaluated through numerical study. Index Terms — Adaptive beamforming, power control, spacedivision multiple access.