Asynchronous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels

This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. To derive decentralized solutions that do not require any cooperation among the users, the optimization problem is formul...

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Vydané v:IEEE transactions on information theory Ročník 54; číslo 7; s. 2868 - 2878
Hlavní autori: Scutari, G., Palomar, D.P., Barbarossa, S.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.07.2008
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Applied sciences
Channels
Decoding
Density
Density measurement
Distributed algorithms
Electronics
Exact sciences and technology
Frequency
Game theory
Games
Gaussian
Gaussian frequency-selective interference channel
Information rates
Information theory
Information, signal and communications theory
Interference
Interference channels
Interference constraints
Iterative algorithms
iterative water-filling algorithm
Maximization
Nash equilibrium
Nash Equilibrium (NE)
Optimization algorithms
Power measurement
Spectra
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
totally asynchronous algorithm
Transmission and modulation (techniques and equipments)
Fading channels
Power spectral density
Information rate
Nash equilibrium
Updating
Iterative method
Power allocation
Game theory
Information transmission
Optimization
Nash Equilib- I rium (NE)
Frequency selection
Decentralized system
totally asynchronous algorithm
Distributed algorithm
Gaussian frequency-selective interference channel
iterative water-filling algorithm
Power spectrum
ISSN:0018-9448, 1557-9654
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Popis
Shrnutí:This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. To derive decentralized solutions that do not require any cooperation among the users, the optimization problem is formulated as a static noncooperative game of complete information. To achieve the so-called Nash equilibria of the game, we propose a new distributed algorithm called asynchronous iterative water-filling algorithm. In this algorithm, the users update their power spectral density (PSD) in a completely distributed and asynchronous way: some users may update their power allocation more frequently than others and they may even use outdated measurements of the received interference. The proposed algorithm represents a unified framework that encompasses and generalizes all known iterative water-filling algorithms, e.g., sequential and simultaneous versions. The main result of the paper consists of a unified set of conditions that guarantee the global converge of the proposed algorithm to the (unique) Nash equilibrium of the game.
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ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2008.924723