Beamforming optimization via max-min SINR in MU-MISO SWIPT systems under bounded channel uncertainty

Zhengyu Zhu; Zhongyong Wang; Zheng Chu; Di Zhang

doi:10.1587/transfun.E99.A.2576

Beamforming optimization via max-min SINR in MU-MISO SWIPT systems under bounded channel uncertainty

Zhengyu Zhu, Zhongyong Wang, Zheng Chu, Di Zhang

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

In this letter, we consider robust beamforming optimization for a multiuser multiple-input single-output system with simultaneous wireless information and power transmission (SWIPT) for the case of imperfect channel state information. Adopting the ellipsoidal uncertainty on channel vector, the robust beamforming design are reformulated as convex semi-definite programming (SDP) by rank-one relaxation. To reduce the complexity, an ellipsoidal uncertainty on channel covariance is studied to derive the equivalent form of original problem. Simulation results are provided to demonstrate the effectiveness of the proposed schemes.

Original language	English
Pages (from-to)	2576-2580
Number of pages	5
Journal	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Volume	E99A
Issue number	12
DOIs	https://doi.org/10.1587/transfun.E99.A.2576
Publication status	Published - 2016 Dec 1

Keywords

Multiuser MISO
Robust optimization
SWIPT

ASJC Scopus subject areas

Signal Processing
Computer Graphics and Computer-Aided Design
Electrical and Electronic Engineering
Applied Mathematics

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10.1587/transfun.E99.A.2576

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title = "Beamforming optimization via max-min SINR in MU-MISO SWIPT systems under bounded channel uncertainty",

abstract = "In this letter, we consider robust beamforming optimization for a multiuser multiple-input single-output system with simultaneous wireless information and power transmission (SWIPT) for the case of imperfect channel state information. Adopting the ellipsoidal uncertainty on channel vector, the robust beamforming design are reformulated as convex semi-definite programming (SDP) by rank-one relaxation. To reduce the complexity, an ellipsoidal uncertainty on channel covariance is studied to derive the equivalent form of original problem. Simulation results are provided to demonstrate the effectiveness of the proposed schemes.",

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author = "Zhengyu Zhu and Zhongyong Wang and Zheng Chu and Di Zhang",

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AU - Zhu, Zhengyu

AU - Wang, Zhongyong

AU - Chu, Zheng

AU - Zhang, Di

PY - 2016/12/1

Y1 - 2016/12/1

N2 - In this letter, we consider robust beamforming optimization for a multiuser multiple-input single-output system with simultaneous wireless information and power transmission (SWIPT) for the case of imperfect channel state information. Adopting the ellipsoidal uncertainty on channel vector, the robust beamforming design are reformulated as convex semi-definite programming (SDP) by rank-one relaxation. To reduce the complexity, an ellipsoidal uncertainty on channel covariance is studied to derive the equivalent form of original problem. Simulation results are provided to demonstrate the effectiveness of the proposed schemes.

AB - In this letter, we consider robust beamforming optimization for a multiuser multiple-input single-output system with simultaneous wireless information and power transmission (SWIPT) for the case of imperfect channel state information. Adopting the ellipsoidal uncertainty on channel vector, the robust beamforming design are reformulated as convex semi-definite programming (SDP) by rank-one relaxation. To reduce the complexity, an ellipsoidal uncertainty on channel covariance is studied to derive the equivalent form of original problem. Simulation results are provided to demonstrate the effectiveness of the proposed schemes.

KW - Multiuser MISO

KW - Robust optimization

KW - SWIPT

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JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

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ER -

Beamforming optimization via max-min SINR in MU-MISO SWIPT systems under bounded channel uncertainty

Abstract

Keywords

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