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A utility-based power-control scheme in wireless cellular systems

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TLDR
This paper presents a power-control framework called utility-based power control (UBPC) by reformulating the problem using a softened SIR requirement (utility) and adding a penalty on power consumption (cost).
Abstract
Distributed power-control algorithms for systems with hard signal-to-interference ratio (SIR) constraints may diverge when infeasibility arises. In this paper, we present a power-control framework called utility-based power control (UBPC) by reformulating the problem using a softened SIR requirement (utility) and adding a penalty on power consumption (cost). Under this framework, the goal is to maximize the net utility, defined as utility minus cost. Although UBPC is still noncooperative and distributed in nature, some degree of cooperation emerges: a user will automatically decrease its target SIR (and may even turn off transmission) when it senses that traffic congestion is building up. This framework enables us to improve system convergence and to satisfy heterogeneous service requirements (such as delay and bit error rate) for integrated networks with both voice users and data users. Fairness, adaptiveness, and a high degree of flexibility can be achieved by properly tuning parameters in UBPC.

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References
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Rate control for communication networks: shadow prices, proportional fairness and stability

TL;DR: This paper analyses the stability and fairness of two classes of rate control algorithm for communication networks, which provide natural generalisations to large-scale networks of simple additive increase/multiplicative decrease schemes, and are shown to be stable about a system optimum characterised by a proportional fairness criterion.
Journal ArticleDOI

A framework for uplink power control in cellular radio systems

TL;DR: It is shown that systems in which transmitter powers are subject to maximum power limitations share these common properties, which permit a general proof of the synchronous and totally asynchronous convergence of the iteration p(t+1)=I(p(t)) to a unique fixed point at which total transmitted power is minimized.
Journal ArticleDOI

Optimization flow control—I: basic algorithm and convergence

TL;DR: An optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates to solve the dual problem using a gradient projection algorithm.
Journal ArticleDOI

A simple distributed autonomous power control algorithm and its convergence

TL;DR: For wireless cellular communication systems, one seeks a simple effective means of power control of signals associated with randomly dispersed users that are reusing a single channel in different cells, and the authors demonstrate exponentially fast convergence to these settings whenever power settings exist for which all users meet the rho requirement.
Journal ArticleDOI

Performance of optimum transmitter power control in cellular radio systems

TL;DR: In order to derive upper performance bounds for transmitter power control schemes, algorithms that are optimum in the sense that the interference probability is minimized are suggested.
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