The Experts below are selected from a list of 39168 Experts worldwide ranked by ideXlab platform
Byonghyo Shim - One of the best experts on this subject based on the ideXlab platform.
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a mmse vector precoding with block diagonalization for multiuser mimo downlink
IEEE Transactions on Communications, 2012Co-Authors: Jungyong Park, Byungju Lee, Byonghyo ShimAbstract:Block diagonalization (BD) algorithm is a generalization of the channel inversion that converts multiuser multi-input multi-output (MIMO) broadcast channel into single-user MIMO channel without inter-user interference. In this paper, we combine the BD technique with a minimum mean square error vector precoding (MMSE-VP) for achieving further gain in performance with minimal computational overhead. Two key ingredients to make our approach effective are the QR decomposition based block diagonalization and joint optimization of transmitter and receiver parameters in the MMSE sense. In fact, by optimizing precoded signal vector and perturbation vector in the transmitter and receiver jointly, we pursue an optimal balance between the residual interference mitigation and the Noise Enhancement suppression. From the sum rate analysis as well as the bit error rate simulations (both uncoded and coded cases) in realistic multiuser MIMO downlink, we show that the proposed BD-MVP brings substantial performance gain over existing multiuser MIMO algorithms.
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a mmse vector precoding with block diagonalization for multiuser mimo downlink
International Conference on Communications, 2011Co-Authors: Jungyong Park, Byungju Lee, Byonghyo ShimAbstract:Block Diagonalization (BD) algorithm is a generalization of channel inversion scheme in multiuser multi-input multi-output (MIMO) broadcast channels. Although the BD algorithm is effective in removing interuser interference, it has a drawback that additional information should be delivered to the receiver. Recent work on BD with vector perturbation (VP) avoids the need for additional information and hence reduces receiver complexity. In this paper, we propose a method achieving further gain in the BD for multiuser MIMO downlink. By combining the BD and minimum mean square error vector precoding (MMSEVP), we pursue the balance between the interference suppression and the Noise Enhancement control, resulting in considerable improvement in the effective SINR. In fact, simulation results on the realistic multiuser downlink scenario show that the proposed method brings substantial performance gain over existing multiuser MIMO algorithms (BD, BD-VP and BD-WF).
Wolfgang Utschick - One of the best experts on this subject based on the ideXlab platform.
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minimum mean square error vector precoding
European Transactions on Telecommunications, 2008Co-Authors: D A Schmidt, M Joham, Wolfgang UtschickAbstract:We derive the minimum mean square error (MMSE) solution to vector precoding for frequency flat multiuser scenarios with a centralised multi-antenna transmitter. The receivers employ a modulo operation, giving the transmitter the additional degree of freedom to choose a perturbation vector. Similar to existing vector precoding techniques, the optimum perturbation vector is found with a closest point search in a lattice. The proposed MMSE vector precoder does not, however, search for the perturbation vector resulting in the lowest unscaled transmit power, as proposed in all previous contributions on vector precoding, but finds an optimum compromise between Noise Enhancement and residual interference. We present simulation results showing that the proposed technique outperforms existing vector precoders, as well as the MMSE Tomlinson-Harashima precoder, and compare the turbo-coded performance to the capacity of the broadcast channel. Copyright © 2007 John Wiley & Sons, Ltd.
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minimum mean square error vector precoding
Personal Indoor and Mobile Radio Communications, 2005Co-Authors: D A Schmidt, M Joham, Wolfgang UtschickAbstract:We derive the minimum mean square error (MMSE) solution to vector precoding for frequency flat multiuser scenarios with a centralized multi-antenna transmitter. The receivers employ a modulo operation, giving the transmitter the additional degree of freedom to choose a perturbation vector. Similar to existing vector precoding techniques, the optimum perturbation vector is found with a closest point search in a lattice. The proposed MMSE vector precoder does not, however, search for the perturbation vector resulting in the lowest transmit energy, as proposed in all previous contributions on vector precoding, but finds an optimum compromise between Noise Enhancement and residual interference. We present simulation results showing that the proposed technique outperforms existing vector precoders, as well as the MMSE Tomlinson-Harashima precoder
Jungyong Park - One of the best experts on this subject based on the ideXlab platform.
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a mmse vector precoding with block diagonalization for multiuser mimo downlink
IEEE Transactions on Communications, 2012Co-Authors: Jungyong Park, Byungju Lee, Byonghyo ShimAbstract:Block diagonalization (BD) algorithm is a generalization of the channel inversion that converts multiuser multi-input multi-output (MIMO) broadcast channel into single-user MIMO channel without inter-user interference. In this paper, we combine the BD technique with a minimum mean square error vector precoding (MMSE-VP) for achieving further gain in performance with minimal computational overhead. Two key ingredients to make our approach effective are the QR decomposition based block diagonalization and joint optimization of transmitter and receiver parameters in the MMSE sense. In fact, by optimizing precoded signal vector and perturbation vector in the transmitter and receiver jointly, we pursue an optimal balance between the residual interference mitigation and the Noise Enhancement suppression. From the sum rate analysis as well as the bit error rate simulations (both uncoded and coded cases) in realistic multiuser MIMO downlink, we show that the proposed BD-MVP brings substantial performance gain over existing multiuser MIMO algorithms.
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a mmse vector precoding with block diagonalization for multiuser mimo downlink
International Conference on Communications, 2011Co-Authors: Jungyong Park, Byungju Lee, Byonghyo ShimAbstract:Block Diagonalization (BD) algorithm is a generalization of channel inversion scheme in multiuser multi-input multi-output (MIMO) broadcast channels. Although the BD algorithm is effective in removing interuser interference, it has a drawback that additional information should be delivered to the receiver. Recent work on BD with vector perturbation (VP) avoids the need for additional information and hence reduces receiver complexity. In this paper, we propose a method achieving further gain in the BD for multiuser MIMO downlink. By combining the BD and minimum mean square error vector precoding (MMSEVP), we pursue the balance between the interference suppression and the Noise Enhancement control, resulting in considerable improvement in the effective SINR. In fact, simulation results on the realistic multiuser downlink scenario show that the proposed method brings substantial performance gain over existing multiuser MIMO algorithms (BD, BD-VP and BD-WF).
E Geraniotis - One of the best experts on this subject based on the ideXlab platform.
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maximum signal to Noise ratio array processing for space time coded systems
IEEE Transactions on Communications, 2002Co-Authors: E GeraniotisAbstract:We consider the design of an array processor for space-time coded multi-antenna systems. As an alternative to the previously proposed zero-forcing method, in this paper, the maximum signal-to-Noise ratio (SNR) criterion is used to obtain a balance between interference suppression and Noise Enhancement. Although the same in concept, this work differs from the conventional minimum mean-squared error method in that there is more than one desired signal dimension each corresponding to one of the space-time coded streams. It is shown that the number of linear filters required by the maximum SNR array processor is no more than the dimension of the signal space or the number of collaborating transmit antennas. The advantages of this design are highly improved performance and reduced decoding complexity.
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maximum signal to Noise ratio array processing for space time coded systems
Personal Indoor and Mobile Radio Communications, 2000Co-Authors: E GeraniotisAbstract:We consider the design of array processor for space-time coded multi-antenna systems. While the zero-forcing method was employed by Tarokh, Naguib, Seshadri and Calderbank (see IEEE Transactions on Information Theory, vol.45, no.4, p.1121-28, 1999), in this paper we seek to obtain a balance between interference suppression and Noise Enhancement. Although same in concept, this work differs from the conventional minimum mean square error (MMSE) method in that there are more than one desired signal dimensions each corresponding to one of the space-time coded streams. In this case, minimizing the mean squared error (MSE) involves averaging over data modulation and may complicate the presentation. Instead, maximizing the signal-to-Noise ratio (SNR) can be handled more concisely. It will be shown that the number of linear filters required by the maximum SNR array processor is no more than the dimension of the signal space or the number of collaborating transmit antennas. The advantages of this design are highly improved performance and reduced decoding complexity.
Klaas P Pruessmann - One of the best experts on this subject based on the ideXlab platform.
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parallel imaging performance as a function of field strength an experimental investigation using electrodynamic scaling
Magnetic Resonance in Medicine, 2004Co-Authors: Florian Wiesinger, Pierrefrancois Van De Moortele, Gregor Adriany, Nicola De Zanche, Kamil Ugurbil, Klaas P PruessmannAbstract:In this work, the dependence of parallel MRI performance on main magnetic field strength is experimentally investigated. Using the general framework of electrodynamic scaling, the B0-dependent behavior of the relevant radiofrequency fields at a single physical field strength of 7 T is studied. In the chosen implementation this is accomplished by adjusting the permittivity and conductivity of a homogeneous spherical phantom. With different mixing ratios of decane, ethanol, purified water, N-methylformamide, and sodium chloride, field strengths in the range of 1.5 to 11.5 T are mimicked. Based on sensitivity maps of an eight-coil receiver array, the field-dependent performance of parallel imaging is assessed in terms of the geometry factor g, which reflects Noise Enhancement in parallel imaging reconstruction. At low field strengths the SNR penalty was nearly independent of B0 and favorably low for 1D reduction factors up to between 3 and 4. At higher field strengths the transition between favorable and prohibitive parallel imaging conditions was found to shift toward higher feasible reduction factors. These findings are in good agreement with previous theoretical predictions. From this agreement it is concluded that parallel MRI at high B0 benefits specifically from onsetting far-field behavior of the involved radiofrequency fields. Magn Reson Med 52:953–964, 2004. © 2004 Wiley-Liss, Inc.
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parallel imaging performance as a function of field strength an experimental investigation using electrodynamic scaling
Magnetic Resonance in Medicine, 2004Co-Authors: Florian Wiesinger, Gregor Adriany, Nicola De Zanche, Kamil Ugurbil, Pierrefrancois Van De Moortele, Klaas P PruessmannAbstract:In this work, the dependence of parallel MRI performance on main magnetic field strength is experimentally investigated. Using the general framework of electrodynamic scaling, the B0-dependent behavior of the relevant radiofrequency fields at a single physical field strength of 7 T is studied. In the chosen implementation this is accomplished by adjusting the permittivity and conductivity of a homogeneous spherical phantom. With different mixing ratios of decane, ethanol, purified water, N-methylformamide, and sodium chloride, field strengths in the range of 1.5 to 11.5 T are mimicked. Based on sensitivity maps of an eight-coil receiver array, the field-dependent performance of parallel imaging is assessed in terms of the geometry factor g, which reflects Noise Enhancement in parallel imaging reconstruction. At low field strengths the SNR penalty was nearly independent of B0 and favorably low for 1D reduction factors up to between 3 and 4. At higher field strengths the transition between favorable and prohibitive parallel imaging conditions was found to shift toward higher feasible reduction factors. These findings are in good agreement with previous theoretical predictions. From this agreement it is concluded that parallel MRI at high B0 benefits specifically from onsetting far-field behavior of the involved radiofrequency fields.