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Sparse Estimation: An MMSE Approach
Constructive Approximation, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pang, Tongyao, Shen, Zuowei
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Single-node MMSE for MMSE cooperative positioning
SPIE Proceedings, 2011ABSTRACT We proposed in our previous work an iterative minimum-mean-square-error (MMSE) cooperative positioningalgorithm. MMSE cooperative positioning method achieves better root-mean-square-error (RMSE) performancethan existing classical estimators. And it is implemented in an iterative pattern so as to circumvent the intensecomputation burden of the ...
Songnan Xi +3 more
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2010 IEEE International Symposium on Information Theory, 2010
We show that the minimum mean-square error (MMSE) of estimating the input based on the channel output is a concave functional of the input-output joint distribution, and its various regularity properties are explored. In particular, the MMSE in Gaussian channels is shown to be weakly continuous in the input distribution and Lipschitz continuous with ...
Yihong Wu 0001, Sergio Verdú
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We show that the minimum mean-square error (MMSE) of estimating the input based on the channel output is a concave functional of the input-output joint distribution, and its various regularity properties are explored. In particular, the MMSE in Gaussian channels is shown to be weakly continuous in the input distribution and Lipschitz continuous with ...
Yihong Wu 0001, Sergio Verdú
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MMSE detection of multi-carrier CDMA
MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341), 2000Minimum mean-squared error (MMSE) detection of multi-carrier code-division multiple-access (CDMA) signals is investigated in this paper. The performance of two different design strategies for MMSE detection is compared. In one case, the MMSE filters are designed separately for each carrier while in the other case the optimization of the filters is done
Scott L. Miller, Bradley J. Rainbolt
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Downlink MMSE Transceiver Optimization for Multiuser MIMO Systems: MMSE Balancing
IEEE Transactions on Signal Processing, 2008We study the problem of mean square error (MSE) transceiver design for point-to-multipoint transmission in multiuser multiple-input-multiple-output (MIMO) systems. We focus on four optimization problems: minimizing the maximum weighted layer-wise or user-wise MSE under a total power constraint; minimizing the total transmit power subject to a set of ...
Shuying Shi +2 more
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Deep Weighted MMSE Downlink Beamforming
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021The weighted minimum mean square error (WMMSE) algorithm was proposed to provide a locally optimum solution to the otherwise NP-hard weighted sum rate maximization beamforming problem, but it can still be prohibitively complex for real-time implementation. With the success of deep unfolding in trading off complexity and performance, we propose to apply
Lissy Pellaco +2 more
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A MMSE estimate for demosaicking
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002Digital color cameras sample the continuous color spectrum using three or more filters; however, each pixel represents a sample of only one of the color bands. This arrangement is called a mosaic. To produce a full resolution color image, the recorded image must be processed to estimate the values of the pixels for all the other color bands.
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Properties of the MMSE of “bad” codes
2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2011We examine non-optimal codes (alternatively referred to as “bad” codes), over the additive Gaussian noise channel. These codes are required to attain a minimum rate at a specific signal-to-noise ratio (snr). For these codes, we provide a tight lower bound on the minimum mean square error (MMSE), valid for any snr, attainable by superposition codebooks,
Ronit Bustin, Shlomo Shamai
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2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, 2011
We develop a novel, microwave beamforming algorithm based on the minimum mean-square error (MMSE) criterion. Relative to perturbation algorithms, the proposed method requires only a fraction of weight changes to estimate the beamformer weights, thereby making it more suitable for high-data-rate applications.
Brian Lawrence, Ioannis N. Psaromiligkos
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We develop a novel, microwave beamforming algorithm based on the minimum mean-square error (MMSE) criterion. Relative to perturbation algorithms, the proposed method requires only a fraction of weight changes to estimate the beamformer weights, thereby making it more suitable for high-data-rate applications.
Brian Lawrence, Ioannis N. Psaromiligkos
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On the Limitation of Linear MMSE Detection
IEEE Transactions on Information Theory, 2006This correspondence highlights the performance limitation of linear minimum mean-squared error (mmse) detection in underdetermined vector Gaussian channels (as in overloaded code-division multiple-access (CDMA) systems) where the number of symbols (users) exceeds the signal space dimension (spread factor). It is shown that for such a simple receiver it
Mahesh K. Varanasi +2 more
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