The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform
Sergio Barbarossa - One of the best experts on this subject based on the ideXlab platform.
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asynchronous iterative water filling for gaussian frequency Selective Interference channels
IEEE Transactions on Information Theory, 2008Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract: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and asynchronous way: some users may update their power allocation more frequently than others and they may even use outdated measurements of the received Interference.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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Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels
arXiv: Information Theory, 2008Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract: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 waterfilling algorithm. In this algorithm, the users update their power spectral density 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 waterfilling 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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Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels: A Unified Framework
2007 Information Theory and Applications Workshop, 2007Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract:In this paper we give an overview of recent results on the rate maximization game in the Gaussian frequency- Selective Interference channel. We focus on the competitive maximization of information rates, subject to global power and spectral mask constraints. To achieve the so-called Nash equilibrium points of the game Yu, Ginis and Cioffi proposed the sequential Iterative Waterfilling Algorithm (IWFA), where, at each iteration, the users choose, one after the other, their power allocation to maximize their own information rate, treating the Interference generated by the others as additive colored Gaussian noise. To overcome the potential slow convergence of the sequential update, specially when the number of users is large, the simultaneous IWFA was proposed by the authors, where, at each iteration, all the users update their power allocations simultaneously, rather than sequentially. Recently, the authors showed that both the sequential and the simultaneous IWFAs are just special cases of a more general unified framework, given by the totally asynchronous IWFA. In this more general algorithm, the users update their power spectral density in a completely distributed and asynchronous way. Furthermore, the asynchronous setup includes another form of lack of synchronism where the transmission by the different users contains time and frequency synchronization offsets. A unified set of convergence conditions were provided for the whole class of algorithms obtained from the asynchronous IWFA. Interestingly, there is a key result used in the proof of convergence of the algorithms: an alternative interpretation of the waterfilling operator as a projector.
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simultaneous iterative water filling for gaussian frequency Selective Interference channels
International Symposium on Information Theory, 2006Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract:The sequential Iterative Water-Filling Algorithm (IWFA) proposed by Yu et al. is by now a popular low-complexity algorithm to compute the Nash equilibrium point of the power allocation game in a Gaussian frequency-Selective multiuser Interference channel. The algorithm is based on a distributed sequential updating where, at each iteration, the users choose their power allocation, one after the other. However, this sequential updating strategy may slow down its convergence time excessively when the number of users is high. In this paper, we propose an alternative distributed algorithm, called Simultaneous Iterative Water-Filling Algorithm (SIWFA), where at each iteration, all the users update their power allocations simultaneously, rather than sequentially. This reduces the convergence time considerably, specially when the number of users is large. Our main contribution is to provide a unified set of sufficient conditions for the convergence of both IWFA and SIWFA, that are less stringent than those known in the literature for IWFA. These conditions guarantee the convergence of both algorithms also in the presence of spectral mask constraints imposed on the power allocations of the users.
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ISIT - Simultaneous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels
2006 IEEE International Symposium on Information Theory, 2006Co-Authors: Gesualdo Scutari, D.r. Palomar, Sergio BarbarossaAbstract:The sequential Iterative Water-Filling Algorithm (IWFA) proposed by Yu et al. is by now a popular low-complexity algorithm to compute the Nash equilibrium point of the power allocation game in a Gaussian frequency-Selective multiuser Interference channel. The algorithm is based on a distributed sequential updating where, at each iteration, the users choose their power allocation, one after the other. However, this sequential updating strategy may slow down its convergence time excessively when the number of users is high. In this paper, we propose an alternative distributed algorithm, called Simultaneous Iterative Water-Filling Algorithm (SIWFA), where at each iteration, all the users update their power allocations simultaneously, rather than sequentially. This reduces the convergence time considerably, specially when the number of users is large. Our main contribution is to provide a unified set of sufficient conditions for the convergence of both IWFA and SIWFA, that are less stringent than those known in the literature for IWFA. These conditions guarantee the convergence of both algorithms also in the presence of spectral mask constraints imposed on the power allocations of the users.
Gesualdo Scutari - One of the best experts on this subject based on the ideXlab platform.
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asynchronous iterative water filling for gaussian frequency Selective Interference channels
IEEE Transactions on Information Theory, 2008Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract: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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Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels
arXiv: Information Theory, 2008Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract: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 waterfilling algorithm. In this algorithm, the users update their power spectral density 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 waterfilling 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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Distributed Power Allocation with Rate Constraints in Gaussian Frequency-Selective Interference Channels
2007Co-Authors: Jong-shi Pang, Gesualdo Scutari, Francisco Facchinei, Chaoxiong WangAbstract:This paper considers the minimization of transmit power in Gaussian frequency Selective Interference channels, subject to a rate constraint for each user. To derive decentralized solutions that do not require any cooperation among the users, we formulate this power control problem as a (generalized) Nash equilibrium game. We obtain sufficient conditions that guarantee the existence and nonemptiness of the solution set to our problem. Then, to compute the solutions of the game, we propose two distributed algorithms ∗The work of this author is based on research supported by the National Science Foundation under grant DMI-0516023. †The work of this author is based on research partially supported by the SURFACE project funded by the European Community under Contract IST-4-027187-STP-SURFACE, and by the Italian Ministry of University and Research. ‡The work of this author is based on research supported by the Program PRIN-MIUR 2005 “Innovative Problems and Methods in Nonlinear Optimization”.
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Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels: A Unified Framework
2007 Information Theory and Applications Workshop, 2007Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract:In this paper we give an overview of recent results on the rate maximization game in the Gaussian frequency- Selective Interference channel. We focus on the competitive maximization of information rates, subject to global power and spectral mask constraints. To achieve the so-called Nash equilibrium points of the game Yu, Ginis and Cioffi proposed the sequential Iterative Waterfilling Algorithm (IWFA), where, at each iteration, the users choose, one after the other, their power allocation to maximize their own information rate, treating the Interference generated by the others as additive colored Gaussian noise. To overcome the potential slow convergence of the sequential update, specially when the number of users is large, the simultaneous IWFA was proposed by the authors, where, at each iteration, all the users update their power allocations simultaneously, rather than sequentially. Recently, the authors showed that both the sequential and the simultaneous IWFAs are just special cases of a more general unified framework, given by the totally asynchronous IWFA. In this more general algorithm, the users update their power spectral density in a completely distributed and asynchronous way. Furthermore, the asynchronous setup includes another form of lack of synchronism where the transmission by the different users contains time and frequency synchronization offsets. A unified set of convergence conditions were provided for the whole class of algorithms obtained from the asynchronous IWFA. Interestingly, there is a key result used in the proof of convergence of the algorithms: an alternative interpretation of the waterfilling operator as a projector.
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simultaneous iterative water filling for gaussian frequency Selective Interference channels
International Symposium on Information Theory, 2006Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract:The sequential Iterative Water-Filling Algorithm (IWFA) proposed by Yu et al. is by now a popular low-complexity algorithm to compute the Nash equilibrium point of the power allocation game in a Gaussian frequency-Selective multiuser Interference channel. The algorithm is based on a distributed sequential updating where, at each iteration, the users choose their power allocation, one after the other. However, this sequential updating strategy may slow down its convergence time excessively when the number of users is high. In this paper, we propose an alternative distributed algorithm, called Simultaneous Iterative Water-Filling Algorithm (SIWFA), where at each iteration, all the users update their power allocations simultaneously, rather than sequentially. This reduces the convergence time considerably, specially when the number of users is large. Our main contribution is to provide a unified set of sufficient conditions for the convergence of both IWFA and SIWFA, that are less stringent than those known in the literature for IWFA. These conditions guarantee the convergence of both algorithms also in the presence of spectral mask constraints imposed on the power allocations of the users.
Marc Moonen - One of the best experts on this subject based on the ideXlab platform.
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autonomous spectrum balancing asb for frequency Selective Interference channels
International Symposium on Information Theory, 2006Co-Authors: Jianwei Huang, Raphael Cendrillon, Mung Chiang, Marc MoonenAbstract:For frequency Selective Interference channels where Interference is treated as noise, distributively attaining the boundary of the rate region is an open problem, and is particularly important for broadband DSL access. This paper develops, analyzes, and simulates a new algorithm for power allocation in frequency Selective Interference channels called Autonomous Spectrum Balancing (ASB). It utilizes the concept of a "reference line", which mimics a typical victim line in the Interference channel. Compared with the state-of-the-art Iterative Watefilling and Optimum Spectrum Balancing methods, the ASB algorithm is completely autonomous, has linear complexity in both the number of users and tones, and gives close to near-optimal performance. Convergence of a version of ASB is proven for any number of users.
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ISIT - Autonomous Spectrum Balancing (ASB) for Frequency Selective Interference Channels
2006 IEEE International Symposium on Information Theory, 2006Co-Authors: Jianwei Huang, Raphael Cendrillon, Mung Chiang, Marc MoonenAbstract:For frequency Selective Interference channels where Interference is treated as noise, distributively attaining the boundary of the rate region is an open problem, and is particularly important for broadband DSL access. This paper develops, analyzes, and simulates a new algorithm for power allocation in frequency Selective Interference channels called Autonomous Spectrum Balancing (ASB). It utilizes the concept of a "reference line", which mimics a typical victim line in the Interference channel. Compared with the state-of-the-art Iterative Watefilling and Optimum Spectrum Balancing methods, the ASB algorithm is completely autonomous, has linear complexity in both the number of users and tones, and gives close to near-optimal performance. Convergence of a version of ASB is proven for any number of users.
John G. Seamon - One of the best experts on this subject based on the ideXlab platform.
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Double dissociation of spatial and object visual memory: Evidence from Selective Interference in intact human subjects
Neuropsychologia, 1993Co-Authors: Matthew C. Tresch, Harry M. Sinnamon, John G. SeamonAbstract:Abstract A functional dissociation of the spatial and object visual systems was produced by Selective Interference in intact young adults. Subjects were instructed to remember the location of a dot in a spatial memory test, and the form of an object in an object memory test. As predicted by current notions of dissociable visual systems in the primate, spatial memory was Selectively impaired by a movement discrimination spatial task, whereas object memory was Selectively impaired by a color discrimination object task.
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Double dissociation of spatial and object visual memory: Evidence from Selective Interference in intact human subjects
Neuropsychologia, 1993Co-Authors: Matthew C. Tresch, Harry M. Sinnamon, John G. SeamonAbstract:A functional dissociation of the spatial and object visual systems was produced by Selective Interference in intact young adults. Subjects were instructed to remember the location of a dot in a spatial memory test, and the form of an object memory test. As predicted by current notions of dissociable visual systems in the primate, spatial memory was Selectively impaired by a movement discrimination spatial task, whereas object memory was Selectively impaired by a color discrimination object task.
Daniel P. Palomar - One of the best experts on this subject based on the ideXlab platform.
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asynchronous iterative water filling for gaussian frequency Selective Interference channels
IEEE Transactions on Information Theory, 2008Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract: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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Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels
arXiv: Information Theory, 2008Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract: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 waterfilling algorithm. In this algorithm, the users update their power spectral density 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 waterfilling 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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Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels: A Unified Framework
2007 Information Theory and Applications Workshop, 2007Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract:In this paper we give an overview of recent results on the rate maximization game in the Gaussian frequency- Selective Interference channel. We focus on the competitive maximization of information rates, subject to global power and spectral mask constraints. To achieve the so-called Nash equilibrium points of the game Yu, Ginis and Cioffi proposed the sequential Iterative Waterfilling Algorithm (IWFA), where, at each iteration, the users choose, one after the other, their power allocation to maximize their own information rate, treating the Interference generated by the others as additive colored Gaussian noise. To overcome the potential slow convergence of the sequential update, specially when the number of users is large, the simultaneous IWFA was proposed by the authors, where, at each iteration, all the users update their power allocations simultaneously, rather than sequentially. Recently, the authors showed that both the sequential and the simultaneous IWFAs are just special cases of a more general unified framework, given by the totally asynchronous IWFA. In this more general algorithm, the users update their power spectral density in a completely distributed and asynchronous way. Furthermore, the asynchronous setup includes another form of lack of synchronism where the transmission by the different users contains time and frequency synchronization offsets. A unified set of convergence conditions were provided for the whole class of algorithms obtained from the asynchronous IWFA. Interestingly, there is a key result used in the proof of convergence of the algorithms: an alternative interpretation of the waterfilling operator as a projector.
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simultaneous iterative water filling for gaussian frequency Selective Interference channels
International Symposium on Information Theory, 2006Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract:The sequential Iterative Water-Filling Algorithm (IWFA) proposed by Yu et al. is by now a popular low-complexity algorithm to compute the Nash equilibrium point of the power allocation game in a Gaussian frequency-Selective multiuser Interference channel. The algorithm is based on a distributed sequential updating where, at each iteration, the users choose their power allocation, one after the other. However, this sequential updating strategy may slow down its convergence time excessively when the number of users is high. In this paper, we propose an alternative distributed algorithm, called Simultaneous Iterative Water-Filling Algorithm (SIWFA), where at each iteration, all the users update their power allocations simultaneously, rather than sequentially. This reduces the convergence time considerably, specially when the number of users is large. Our main contribution is to provide a unified set of sufficient conditions for the convergence of both IWFA and SIWFA, that are less stringent than those known in the literature for IWFA. These conditions guarantee the convergence of both algorithms also in the presence of spectral mask constraints imposed on the power allocations of the users.
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Asynchronous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels: A Unified Framework
2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications, 2006Co-Authors: Gesualdo Scutari, Daniel P. Palomar, Sergio BarbarossaAbstract:In this paper we propose a unified framework, based on a new distributed algorithm to compute the Nash equilibrium point of the power allocation game in a frequency-Selective multiuser Interference channel. The proposed scheme is based on a totally asynchronous updating of the power allocation from the users, where some users may change their power allocation more frequently than others and, furthermore, they are allowed to use also outdated version of the Interference. The proposed algorithm contains as special cases the well-known iterative water-filling algorithm, either sequential or simultaneous. Our main contribution is then to provide a unified set of sufficient conditions under which all these algorithms are guaranteed to convergence to the unique Nash equilibrium of the game. These conditions enlarge those existing in the literature for the convergence of the sequential iterative water-filling algorithm.
