Review of some fundamental approaches for power control in wireless networks

Douros, Vaggelis G.; Polyzos, George C.

doi:10.1016/j.comcom.2011.03.001

Cited by 41 publications

(25 citation statements)

References 25 publications

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“…Specifically, Gatsis and Giannakis [24] discuss about the change of variables that are carried out in GP in order to convexify many power control problems. As a summary, in [25,26], the reader can find good reviews on power control in actual wireless networks.…”

Section: Related Work and Contributionsmentioning

confidence: 99%

Distributed power control with received power constraints for time-area-spectrum licenses

et al. 2016

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a b s t r a c tThis paper deals with the problem of optimal decentralized power control in systems whose spectrum is regulated in time and space, the so-called time-area-spectrum (TAS) licensed. In this paper we consider those locations with colliding transmissions; thus, addressing a scenario with full interference. In order to facilitate the coexistence of different TAS licenses, the power spectral density of the used band shall be limited. Since controlling the overall radiated power in a given area is cumbersome, we control the amount of received power. First, we present the achievable rates (i.e. the rate Pareto set) and their corresponding powers by means of multi-criteria optimization theory. Second, we study a completely decentralized and gradient-based power control that obtains Pareto-efficient rates and powers, the so-called DPC-TAS (Decentralized Power Control for TAS). The power control convergence and the possibility of guaranteeing a minimum Quality of Service (QoS) per user are analyzed. Third, in order to gain more insight into the features of DPC-TAS, this paper compares it with other baseline power control approaches. For the sake of comparison, a simple pricing mechanism is proposed. Numerical simulations verify the good performance of DPC-TAS.

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Section: Related Work and Contributionsmentioning

confidence: 99%

Distributed power control with received power constraints for time-area-spectrum licenses

et al. 2016

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“…Since Zander's early work on power control [1], there has been many research studies on the power control in wireless networks (e.g., see [2,3]). Many of power control schemes use the well-known target-SINR-tracking power control algorithm (TPC) wherein each user tries to track a predefined desired target-SINR.…”

Section: Introductionmentioning

confidence: 99%

High-performance SINR assignment in multi-cell wireless networks

Monemi

Zolghadrasli

Golbaharhaghighi

2015

AEU - International Journal of Electronics and Communications

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“…[12,13]. In particular, the standard setup for the feasibility and convergence analysis of power control is the static regime where transient phenomena are cast aside and both the channel conditions (channel gain and noise) and the QoS/QoE requirements of the involved connections are assumed effectively static -in the sense that they evolve slow enough for power control algorithms to converge.…”

Section: Introductionmentioning

confidence: 99%

No regrets: Distributed power control under time-varying channels and QoS requirements

Stiakogiannakis¹,

Mertikopoulos²,

Touati³

2014

2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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The problem of power control in wireless networks consists of adjusting transmit power in order to achieve a target SINR level in the presence of noise and interference from other users. In this paper, we examine the performance of the seminal Foschini-Miljanic (FM) power control scheme in networks where channel conditions and users' quality of service (QoS) requirements vary arbitrarily with time (e.g. due to user mobility, fading, etc.). Contrary to the case of static and/or ergodic channels, the system optimum power configuration may evolve over time in an unpredictable fashion, so users must adapt to changes in the wireless medium (or their own requirements) "on the fly", without being able to anticipate the system evolution. To account for these considerations, we provide a formulation of power control as an online optimization problem and we show that the FM dynamics lead to no regret in this dynamic context. Specifically, in the absence of maximum transmit power constraints, we show that the FM power control scheme performs at least as well as (and typically outperforms) any fixed transmit profile, irrespective of how the system varies with time; finally, to account for maximum power constraints that occur in practice, we introduce an adjusted version of the FM algorithm which retains the convergence and no-regret properties of the original algorithm in this constrained setting.

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Review of some fundamental approaches for power control in wireless networks

Cited by 41 publications

References 25 publications

Distributed power control with received power constraints for time-area-spectrum licenses

Distributed power control with received power constraints for time-area-spectrum licenses

High-performance SINR assignment in multi-cell wireless networks

No regrets: Distributed power control under time-varying channels and QoS requirements

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