Weighted sum rate maximization with multiple linear conic constraints

Hans H. Brunner; Andreas Dotzler; Wolfgang Utschick; Josef A. Nossek

doi:10.1109/ICC.2015.7249054

Weighted sum rate maximization with multiple linear conic constraints

Hans H. Brunner, Andreas Dotzler, Wolfgang Utschick, Josef A. Nossek

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

In the downlink (DL) of a multi-user multiple-input and multiple-output (MU-MIMO) system, the maximization of the weighted sum rate with dirty paper precoding (DPC) is treated under multiple linear and linear conic constraints. By network duality, the problem is transformed to a minimax uplink (UL) problem. In the UL, the minimization of the utility with respect to the noise covariance and the maximization of the utility with respect to the transmit covariances is solved either jointly or alternately with the gradient-projection algorithm. The proposed algorithms do not only allow to find the maximum weighted sum rate with respect to conic constraints, they are also efficient implementations with respect to multiple linear constraints.

Original language	English
Title of host publication	2015 IEEE International Conference on Communications, ICC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4635-4640
Number of pages	6
ISBN (Electronic)	9781467364324
DOIs	https://doi.org/10.1109/ICC.2015.7249054
State	Published - 9 Sep 2015
Event	IEEE International Conference on Communications, ICC 2015 - London, United Kingdom Duration: 8 Jun 2015 → 12 Jun 2015

Publication series

Name	IEEE International Conference on Communications
Volume	2015-September
ISSN (Print)	1550-3607

Conference

Conference	IEEE International Conference on Communications, ICC 2015
Country/Territory	United Kingdom
City	London
Period	8/06/15 → 12/06/15

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10.1109/ICC.2015.7249054

Cite this

Brunner, H. H., Dotzler, A., Utschick, W., & Nossek, J. A. (2015). Weighted sum rate maximization with multiple linear conic constraints. In 2015 IEEE International Conference on Communications, ICC 2015 (pp. 4635-4640). Article 7249054 (IEEE International Conference on Communications; Vol. 2015-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2015.7249054

@inproceedings{efbbe3d2d68a415db9c2c31db2e1d77f,

title = "Weighted sum rate maximization with multiple linear conic constraints",

abstract = "In the downlink (DL) of a multi-user multiple-input and multiple-output (MU-MIMO) system, the maximization of the weighted sum rate with dirty paper precoding (DPC) is treated under multiple linear and linear conic constraints. By network duality, the problem is transformed to a minimax uplink (UL) problem. In the UL, the minimization of the utility with respect to the noise covariance and the maximization of the utility with respect to the transmit covariances is solved either jointly or alternately with the gradient-projection algorithm. The proposed algorithms do not only allow to find the maximum weighted sum rate with respect to conic constraints, they are also efficient implementations with respect to multiple linear constraints.",

author = "Brunner, {Hans H.} and Andreas Dotzler and Wolfgang Utschick and Nossek, {Josef A.}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Communications, ICC 2015 ; Conference date: 08-06-2015 Through 12-06-2015",

year = "2015",

month = sep,

day = "9",

doi = "10.1109/ICC.2015.7249054",

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Brunner, HH, Dotzler, A, Utschick, W & Nossek, JA 2015, Weighted sum rate maximization with multiple linear conic constraints. in 2015 IEEE International Conference on Communications, ICC 2015., 7249054, IEEE International Conference on Communications, vol. 2015-September, Institute of Electrical and Electronics Engineers Inc., pp. 4635-4640, IEEE International Conference on Communications, ICC 2015, London, United Kingdom, 8/06/15. https://doi.org/10.1109/ICC.2015.7249054

Weighted sum rate maximization with multiple linear conic constraints. / Brunner, Hans H.; Dotzler, Andreas; Utschick, Wolfgang et al.
2015 IEEE International Conference on Communications, ICC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 4635-4640 7249054 (IEEE International Conference on Communications; Vol. 2015-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Weighted sum rate maximization with multiple linear conic constraints

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AU - Dotzler, Andreas

AU - Utschick, Wolfgang

AU - Nossek, Josef A.

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Y1 - 2015/9/9

N2 - In the downlink (DL) of a multi-user multiple-input and multiple-output (MU-MIMO) system, the maximization of the weighted sum rate with dirty paper precoding (DPC) is treated under multiple linear and linear conic constraints. By network duality, the problem is transformed to a minimax uplink (UL) problem. In the UL, the minimization of the utility with respect to the noise covariance and the maximization of the utility with respect to the transmit covariances is solved either jointly or alternately with the gradient-projection algorithm. The proposed algorithms do not only allow to find the maximum weighted sum rate with respect to conic constraints, they are also efficient implementations with respect to multiple linear constraints.

AB - In the downlink (DL) of a multi-user multiple-input and multiple-output (MU-MIMO) system, the maximization of the weighted sum rate with dirty paper precoding (DPC) is treated under multiple linear and linear conic constraints. By network duality, the problem is transformed to a minimax uplink (UL) problem. In the UL, the minimization of the utility with respect to the noise covariance and the maximization of the utility with respect to the transmit covariances is solved either jointly or alternately with the gradient-projection algorithm. The proposed algorithms do not only allow to find the maximum weighted sum rate with respect to conic constraints, they are also efficient implementations with respect to multiple linear constraints.

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ER -

Weighted sum rate maximization with multiple linear conic constraints

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