The Experts below are selected from a list of 118134 Experts worldwide ranked by ideXlab platform
Stephen Boyd - One of the best experts on this subject based on the ideXlab platform.
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Geometric programming duals of Channel Capacity and rate distortion
IEEE Transactions on Information Theory, 2004Co-Authors: Mung Chiang, Stephen BoydAbstract:We show that the Lagrange dual problems of the Channel Capacity problem with input cost and the rate distortion problem are simple geometric programs. Upper bounds on Channel Capacity and lower bounds on rate distortion can be efficiently generated from their duals. For Channel Capacity, the geometric programming dual characterization is shown to be equivalent to the minmax Kullback-Leibler (KL) characterization in Csiszar et al. (1981). For rate distortion, the geometric programming dual is extended to rate distortion with two-sided state information. A "duality by mapping" is then given between the Lagrange dual problems of Channel Capacity with input cost and rate distortion, which resolves several apparent asymmetries between their primal problems in the familiar form of mutual information optimization problems. Both the primal and dual problems can be interpreted in a common framework of free energy optimization from statistical physics.
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Geometric programming dual of Channel Capacity
IEEE International Symposium on Information Theory 2003. Proceedings., 2003Co-Authors: Mung Chiang, Stephen BoydAbstract:We show that the Lagrange dual of the problem of Channel Capacity with input cost for discrete memoryless Channel is a simple and well- structured geometric program. The geometric pro- gram dual gives a new class of upper bounds of chan- nel Capacity that can be made arbitrarily tight and includes some known bounds as special cases, and a free energy interpretation to Channel Capacity. Geometric programming (21 is a type of nonlinear optimiza- tion useful for various engineering problems such as network resource allocation and analog circuit design. We first define a monomial as a function f : RT -+ R:
Lei Wang - One of the best experts on this subject based on the ideXlab platform.
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On the Channel Capacity of MIMO-OFDM systems
IEEE International Symposium on Communications and Information Technology 2005. ISCIT 2005., 2005Co-Authors: Jun Wang, Shi-hua Zhu, Lei WangAbstract:In order to study the impacts of Channel model parameters including antenna spacing, scattering angle and the amount of delay spread on the Channel Capacity of a MIMO-OFDM (multiple input multiple output; orthogonal frequency division multiplexing) system, a novel method is proposed to explore the Channel Capacity with frequency selective fading. Based on uniform circular antenna at the receiver side, the model of fading spatial correlation is constructed. And also the statistical properties of the space-time Channel are investigated. Then using the properties of Wishart distribution, the Channel Capacity and its upper and lower bounds for MIMO OFDM systems with arbitrary number of antennas are derived for the case where the Channel is unknown at the transmitter and perfectly known at the receiver. Computer simulation results show that the Channel Capacity is maximized when the antenna spacing increases to a certain point, and further more, the larger is the scattering angle, the more quickly the Channel Capacity converges to its maximum. At high SNR, the upper and lower bounds on expected Capacity are close to its real value.
Jun Wang - One of the best experts on this subject based on the ideXlab platform.
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Channel Capacity of MIMO Systems under Correlate Fading Environment
2010 International Conference on Computational Intelligence and Software Engineering, 2010Co-Authors: Jun Wang, Xiaochuan Yu, Qi Yan, Shaoping DengAbstract:In this paper, the Channel Capacity of a Multiple Input Multiple Output (MIMO) system with correlated fading is investigated. The fading correlation model is established and the effects of the number of antennas and the scattering angle on the Channel Capacity are studied. Based on the random theory, the closed-form expression for the Channel Capacity of MIMO system is derived in detail. The simulation results show that the Channel Capacity is determined by the fading correlated matrix. And the Channel Capacity is saturated when the number of the antennas increases to some values。
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On the Channel Capacity of MIMO Systems Under Correlated Rayleigh Fading
2007 International Conference on Wireless Communications Networking and Mobile Computing, 2007Co-Authors: Jun Wang, Jinfang Dou, Quan Zhou, Lede QiuAbstract:In order to study the impacts of Channel model parameters on the Channel Capacity of a multiple input multiple output (MIMO) system, a novel method is proposed to explore the Channel Capacity under Rayleigh flat fading with correlated transmit and correlated receive antennas. The optimal transmitting direction which can achieve maximum Channel Capacity is derived in detail using random matrices theory. At high SNR, the closed-form expression for the Channel Capacity of MIMO system is given by using the properties of Wishart distribution. Computer simulation results show that the Channel Capacity is maximized when the antenna spacing increases to a certain point. At high SNR, the estimation of Channel Capacity is close to its true value. And when the same array configuration is adopted both at the transmitter and the receiver, the UCA yields higher Channel Capacity than ULA.
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On the Channel Capacity of MIMO-OFDM systems
IEEE International Symposium on Communications and Information Technology 2005. ISCIT 2005., 2005Co-Authors: Jun Wang, Shi-hua Zhu, Lei WangAbstract:In order to study the impacts of Channel model parameters including antenna spacing, scattering angle and the amount of delay spread on the Channel Capacity of a MIMO-OFDM (multiple input multiple output; orthogonal frequency division multiplexing) system, a novel method is proposed to explore the Channel Capacity with frequency selective fading. Based on uniform circular antenna at the receiver side, the model of fading spatial correlation is constructed. And also the statistical properties of the space-time Channel are investigated. Then using the properties of Wishart distribution, the Channel Capacity and its upper and lower bounds for MIMO OFDM systems with arbitrary number of antennas are derived for the case where the Channel is unknown at the transmitter and perfectly known at the receiver. Computer simulation results show that the Channel Capacity is maximized when the antenna spacing increases to a certain point, and further more, the larger is the scattering angle, the more quickly the Channel Capacity converges to its maximum. At high SNR, the upper and lower bounds on expected Capacity are close to its real value.
Mung Chiang - One of the best experts on this subject based on the ideXlab platform.
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Geometric programming duals of Channel Capacity and rate distortion
IEEE Transactions on Information Theory, 2004Co-Authors: Mung Chiang, Stephen BoydAbstract:We show that the Lagrange dual problems of the Channel Capacity problem with input cost and the rate distortion problem are simple geometric programs. Upper bounds on Channel Capacity and lower bounds on rate distortion can be efficiently generated from their duals. For Channel Capacity, the geometric programming dual characterization is shown to be equivalent to the minmax Kullback-Leibler (KL) characterization in Csiszar et al. (1981). For rate distortion, the geometric programming dual is extended to rate distortion with two-sided state information. A "duality by mapping" is then given between the Lagrange dual problems of Channel Capacity with input cost and rate distortion, which resolves several apparent asymmetries between their primal problems in the familiar form of mutual information optimization problems. Both the primal and dual problems can be interpreted in a common framework of free energy optimization from statistical physics.
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Geometric programming dual of Channel Capacity
IEEE International Symposium on Information Theory 2003. Proceedings., 2003Co-Authors: Mung Chiang, Stephen BoydAbstract:We show that the Lagrange dual of the problem of Channel Capacity with input cost for discrete memoryless Channel is a simple and well- structured geometric program. The geometric pro- gram dual gives a new class of upper bounds of chan- nel Capacity that can be made arbitrarily tight and includes some known bounds as special cases, and a free energy interpretation to Channel Capacity. Geometric programming (21 is a type of nonlinear optimiza- tion useful for various engineering problems such as network resource allocation and analog circuit design. We first define a monomial as a function f : RT -+ R:
Hideki Ochiai - One of the best experts on this subject based on the ideXlab platform.
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Channel Capacity of clipped OFDM systems
2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060), 2000Co-Authors: Hideki OchiaiAbstract:The Channel Capacity of OFDM systems with digital clipping is discussed, under the assumption that the distortion terms are Gaussian-distributed.