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Duality, achievable rates, and sumrate capacity of Gaussian MIMO broadcast channels
 IEEE TRANS. INFORM. THEORY
, 2003
"... We consider a multiuser multipleinput multipleoutput (MIMO) Gaussian broadcast channel (BC), where the transmitter and receivers have multiple antennas. Since the MIMO BC is in general a nondegraded BC, its capacity region remains an unsolved problem. In this paper, we establish a duality between ..."
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Cited by 339 (21 self)
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paper achievable region for the MIMO BC. We also show that the dirty paper achievable region achieves the sumrate capacity of the MIMO BC by establishing that the maximum sum rate of this region equals an upper bound on the sum rate of the MIMO BC.
On the SumRate of MIMO Interference Channel
"... Abstract—The problem of maximizing the sumrate of a MIMO interference channel is investigated. Each receiver node is assumed to perform single user detection by treating interference from other users as Gaussian noise. It is assumed that all the users share a single frequency band and no precoding ..."
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Abstract—The problem of maximizing the sumrate of a MIMO interference channel is investigated. Each receiver node is assumed to perform single user detection by treating interference from other users as Gaussian noise. It is assumed that all the users share a single frequency band and no pre
Factor Graphs and the SumProduct Algorithm
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
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Cited by 1787 (72 self)
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computational rule, the sumproduct algorithm operates in factor graphs to computeeither exactly or approximatelyvarious marginal functions by distributed messagepassing in the graph. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can
Sum Rate of Multiterminal Gaussian Source Coding
 DIMACS SERIES IN DISCRETE MATHEMATICS AND THEORETICAL COMPUTER SCIENCE
"... We characterize the sum rate of a class of multiterminal Gaussian source coding problems with quadratic distortion constraints. The key component of the solution is the identification of a multiple antenna broadcast channel that serves as a test channel. ..."
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Cited by 9 (0 self)
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We characterize the sum rate of a class of multiterminal Gaussian source coding problems with quadratic distortion constraints. The key component of the solution is the identification of a multiple antenna broadcast channel that serves as a test channel.
A new outer bound and the noisyinterference sumrate capacity for Gaussian interference channels
 IEEE International Symposium on Information Theory
, 2008
"... Abstract — A new outer bound on the capacity region of Gaussian interference channels is developed. The bound combines and improves existing genieaided methods and is shown to give the sumrate capacity for Gaussian interference channel with noisy interference as defined in this paper. Specifically ..."
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Cited by 163 (10 self)
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Abstract — A new outer bound on the capacity region of Gaussian interference channels is developed. The bound combines and improves existing genieaided methods and is shown to give the sumrate capacity for Gaussian interference channel with noisy interference as defined in this paper
Maximizing Sum Rates in Gaussian Interferencelimited Channels
, 2008
"... We study the problem of maximizing sum rates in Gaussian interferencelimited channels. We show that this maximum problem can be restated as a maximization problem of a convex function on a closed convex set. We suggest three algorithms to find the exact and approximate values of the optimal rates. ..."
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Cited by 2 (2 self)
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We study the problem of maximizing sum rates in Gaussian interferencelimited channels. We show that this maximum problem can be restated as a maximization problem of a convex function on a closed convex set. We suggest three algorithms to find the exact and approximate values of the optimal rates.
Minimum Error Rate Training in Statistical Machine Translation
, 2003
"... Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training cri ..."
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Cited by 663 (7 self)
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Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training criteria which directly optimize translation quality.
On the Maximum SumRate of Cognitive MIMO Interference Channels
"... Abstract—In this paper, we address the problem of maximizing the ergodic sumrate of an Nuser cognitive MIMO Interference Channel (IC) formed by unlicensed (or secondary) users. We assume that N secondary users coexist in the same area and try to access the same set of frequency bands. In such a se ..."
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Abstract—In this paper, we address the problem of maximizing the ergodic sumrate of an Nuser cognitive MIMO Interference Channel (IC) formed by unlicensed (or secondary) users. We assume that N secondary users coexist in the same area and try to access the same set of frequency bands. In such a
Results 1  10
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1,455,100