Weighted Sum-Rate Maximization Using Weighted MMSE for MIMO-BC Beamforming Design

Søren Christensen; Elisabeth De Carvalho; Rajiv Agarwal; John M. Cioffi

doi:10.1109/ICC.2009.5199574

Weighted Sum-Rate Maximization Using Weighted MMSE for MIMO-BC Beamforming Design

Søren Christensen, Elisabeth De Carvalho, Rajiv Agarwal, John M. Cioffi

Department of Electronic Systems

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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Abstract

This paper studies linear transmit filter design for weighted sum-rate (WSR) maximization in the multiple input multiple output broadcast channel (MIMO-BC). The problem of finding the optimal transmit filter is non-convex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and Minimum Mean Square Error (MMSE), this paper establishes a relationship between weighted sum-rate and weighted MMSE in the MIMO-BC. The relationship is used to propose a low complexity algorithm for finding a local weighted sum-rate optimum based on alternating optimization. Numerical results studying sum-rate show that the proposed algorithm achieves high performance with few iterations.

Original language	English
Title of host publication	IEEE International Conference on Communications, 2009. ICC '09
Number of pages	6
Publisher	IEEE
Publication date	2009
ISBN (Electronic)	978-1-4244-3435-0
DOIs	https://doi.org/10.1109/ICC.2009.5199574
Publication status	Published - 2009
Event	IEEE International Conference on Communications - Dresden, Germany Duration: 14 Jun 2009 → 18 Jul 2009

Conference

Conference	IEEE International Conference on Communications
Country/Territory	Germany
City	Dresden
Period	14/06/2009 → 18/07/2009

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@inproceedings{c29dd0e0067f11df9142000ea68e967b,

title = "Weighted Sum-Rate Maximization Using Weighted MMSE for MIMO-BC Beamforming Design",

abstract = "This paper studies linear transmit filter design for weighted sum-rate (WSR) maximization in the multiple input multiple output broadcast channel (MIMO-BC). The problem of finding the optimal transmit filter is non-convex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and Minimum Mean Square Error (MMSE), this paper establishes a relationship between weighted sum-rate and weighted MMSE in the MIMO-BC. The relationship is used to propose a low complexity algorithm for finding a local weighted sum-rate optimum based on alternating optimization. Numerical results studying sum-rate show that the proposed algorithm achieves high performance with few iterations.",

author = "S{\o}ren Christensen and {De Carvalho}, Elisabeth and Rajiv Agarwal and Cioffi, {John M.}",

year = "2009",

doi = "10.1109/ICC.2009.5199574",

language = "English",

booktitle = "IEEE International Conference on Communications, 2009. ICC '09",

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T1 - Weighted Sum-Rate Maximization Using Weighted MMSE for MIMO-BC Beamforming Design

AU - Christensen, Søren

AU - De Carvalho, Elisabeth

AU - Agarwal, Rajiv

AU - Cioffi, John M.

PY - 2009

Y1 - 2009

N2 - This paper studies linear transmit filter design for weighted sum-rate (WSR) maximization in the multiple input multiple output broadcast channel (MIMO-BC). The problem of finding the optimal transmit filter is non-convex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and Minimum Mean Square Error (MMSE), this paper establishes a relationship between weighted sum-rate and weighted MMSE in the MIMO-BC. The relationship is used to propose a low complexity algorithm for finding a local weighted sum-rate optimum based on alternating optimization. Numerical results studying sum-rate show that the proposed algorithm achieves high performance with few iterations.

AB - This paper studies linear transmit filter design for weighted sum-rate (WSR) maximization in the multiple input multiple output broadcast channel (MIMO-BC). The problem of finding the optimal transmit filter is non-convex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and Minimum Mean Square Error (MMSE), this paper establishes a relationship between weighted sum-rate and weighted MMSE in the MIMO-BC. The relationship is used to propose a low complexity algorithm for finding a local weighted sum-rate optimum based on alternating optimization. Numerical results studying sum-rate show that the proposed algorithm achieves high performance with few iterations.

U2 - 10.1109/ICC.2009.5199574

DO - 10.1109/ICC.2009.5199574

M3 - Article in proceeding

BT - IEEE International Conference on Communications, 2009. ICC '09

PB - IEEE

T2 - IEEE International Conference on Communications

Y2 - 14 June 2009 through 18 July 2009

ER -

Weighted Sum-Rate Maximization Using Weighted MMSE for MIMO-BC Beamforming Design

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