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Analysis of iterative waterfilling algorithm for multiuser power control in digital subscriber lines

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TLDR
Based on this LCP reformulation, the linear convergence of the popular distributed iterative waterfilling algorithm (IWFA) is established for arbitrary symmetric interference environment and for certain asymmetric channel conditions with any number of users.
Abstract
We present an equivalent linear complementarity problem (LCP) formulation of the noncooperative Nash game resulting from the DSL power control problem. Based on this LCP reformulation, we establish the linear convergence of the popular distributed iterative waterfilling algorithm (IWFA) for arbitrary symmetric interference environment and for certain asymmetric channel conditions with any number of users. In the case of symmetric interference crosstalk coefficients, we show that the users of IWFA in fact, unknowingly but willingly, cooperate to minimize a common quadratic cost function whose gradient measures the received signal power from all users. This is surprising since the DSL users in the IWFA have no intention to cooperate as each maximizes its own rate to reach a Nash equilibrium. In the case of asymmetric coefficients, the convergence of the IWFA is due to a contraction property of the iterates. In addition, the LCP reformulation enables us to solve the DSL power control problem under no restrictions on the interference coefficients using existing LCP algorithms, for example, Lemke's method. Indeed, we use the latter method to benchmark the empirical performance of IWFA in the presence of strong crosstalk interference.

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Citations
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Proceedings ArticleDOI

An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel

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An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel

TL;DR: A linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean-square error (MSE) and can be extended to a general class of sum-utility maximization problem.
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Dynamic Spectrum Management: Complexity and Duality

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Convex Optimization, Game Theory, and Variational Inequality Theory

TL;DR: A unified view of some basic theoretical foundations and main techniques in convex optimization, game theory, and VI theory is provided, putting special emphasis on the generality of the VI framework, showing how it allows to tackle several interesting problems in nonlinear analysis, classical optimization, and equilibrium programming.
References
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Book

Parallel and Distributed Computation: Numerical Methods

TL;DR: This work discusses parallel and distributed architectures, complexity measures, and communication and synchronization issues, and it presents both Jacobi and Gauss-Seidel iterations, which serve as algorithms of reference for many of the computational approaches addressed later.
Book

Finite-Dimensional Variational Inequalities and Complementarity Problems

TL;DR: Newton Methods for Nonsmooth Equations as mentioned in this paper and global methods for nonsmooth equations were used to solve the Complementarity problem in the context of non-complementarity problems.
Book

The Linear Complementarity Problem

TL;DR: In this article, the authors present an overview of existing and multiplicity of degree theory and propose pivoting methods and iterative methods for degree analysis, including sensitivity and stability analysis.
Journal ArticleDOI

Über ein Paradoxon aus der Verkehrsplanung

TL;DR: It is indicated by an example that an extension of the road network may cause a redistribution of the traffic which results in longer individual running times.
Journal ArticleDOI

Bimatrix Equilibrium Points and Mathematical Programming

C. E. Lemke
- 01 May 1965 - 
TL;DR: In this paper, simple constructive proofs are given of solutions to the matric matric system Mz − ω = q; z ≧ 0; ω ≧ 1; zT = 0, for various kinds of data M, q, which embrace quadratic programming and the problem of finding equilibrium points of bimatrix games.
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