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Robust Transceiver Design for Multiuser MIMO Downlink with Channel Uncertainties

Wei MIAO, Yunzhou LI, Xiang CHEN, Shidong ZHOU, Jing WANG

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Wei MIAO
State Key Laboratory on Microwave and Digital Communications, Tsinghua National Laboratory for Information Science and Technology
Department of Electronic Engineering, Tsinghua University
The Institute of Electronics, Information and Communication Engineers
Yunzhou LI
State Key Laboratory on Microwave and Digital Communications, Tsinghua National Laboratory for Information Science and Technology
Department of Electronic Engineering, Tsinghua University
Xiang CHEN
State Key Laboratory on Microwave and Digital Communications, Tsinghua National Laboratory for Information Science and Technology
Department of Electronic Engineering, Tsinghua University
The Institute of Electronics, Information and Communication Engineers
Shidong ZHOU
State Key Laboratory on Microwave and Digital Communications, Tsinghua National Laboratory for Information Science and Technology
Department of Electronic Engineering, Tsinghua University
Jing WANG
State Key Laboratory on Microwave and Digital Communications, Tsinghua National Laboratory for Information Science and Technology
Department of Electronic Engineering, Tsinghua University

Corresponding author

Keywords:multiuser MIMO,downlink,transceiver,robust design

JOURNALRESTRICTED ACCESS

2008 Volume E91.BIssue 10Pages 3351-3354

DOIhttps://doi.org/10.1093/ietcom/e91-b.10.3351

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Published: October 01, 2008Received: October 16, 2007Available on J-STAGE: March 01, 2010Accepted: -Advance online publication: -Revised: -

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Article overview

Abstract

This letter addresses the problem of robust transceiver design for the multiuser multiple-input-multiple-output (MIMO) downlink where the channel state information at the base station (BS) is imperfect. A stochastic approach which minimizes the expectation of the total mean square error (MSE) of the downlink conditioned on the channel estimates under a total transmit power constraint is adopted. The iterative algorithm reported in [2] is improved to handle the proposed robust optimization problem. Simulation results show that our proposed robust scheme effectively reduces the performance loss due to channel uncertainties and outperforms existing methods, especially when the channel errors of the users are different.

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