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C. Xing, Niwei Wang, Jiqing Ni, Zesong Fei, Jingming Kuang (2013)
MIMO Beamforming Designs With Partial CSI Under Energy Harvesting ConstraintsIEEE Signal Processing Letters, 20
Rui Zhang, Chin Ho (2011)
MIMO Broadcasting for Simultaneous Wireless Information and Power TransferIEEE Transactions on Wireless Communications, 12
(1999)
He is currently an Associate Professor with the School of Electronics and Information Technology
RA Horn, CR Johnson (1995)
Matrix Analysis
(2009)
He is currently a lecturer with the School of Data and Computer Science, SYSU. His research interests are in wireless communications powered by energy harvesting
Zhengzheng Xiang, M. Tao (2012)
Robust Beamforming for Wireless Information and Power TransmissionIEEE Wireless Communications Letters, 1
A. Beck, Yonina Eldar (2006)
Strong Duality in Nonconvex Quadratic Optimization with Two Quadratic ConstraintsSIAM J. Optim., 17
R. Muthalagu, P. Muthuchidambaranathan (2014)
Multiuser MIMO Transceiver Design for Uplink and Downlink with Imperfect CSIWireless Personal Communications, 75
N. Vučić, H. Boche, Shuying Shi (2008)
Robust Transceiver Optimization in Downlink Multiuser MIMO Systems with Channel Uncertainty2008 IEEE International Conference on Communications
N Vuc̆ić, H Boche, S Shi (2009)
Robust transceiver optimization in downlink multiuser MIMO systemsIEEE Transactions on Signal Processing, 57
E. Yaz (1998)
Linear Matrix Inequalities In System And Control TheoryProceedings of the IEEE, 86
Stephen Boyd, L. Vandenberghe (2005)
Convex OptimizationJournal of the American Statistical Association, 100
P. Ubaidulla, A. Chockalingam (2008)
Robust Transceiver Design for Multiuser MIMO DownlinkIEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference
In this paper, considering the simultaneous wireless information and power transfer scheme, we investigate the robust transceiver design in the multiuser multiple-input–multiple-output system with the energy harvesting constraints where the channel uncertainties are modeled by the worst-case model. We formulate the robust transceiver design problem as a worst-case mean-square-error (MSE) minimization problem where the transmit covariance matrix at the transmitter and the preprocessing matrices at the information-decoding (ID) receivers are alternatively optimized. With the known preprocessing matrices at the ID receivers, the transmit covariance matrix optimization problem is transformed into a semidefinite programming (SDP) by employing the $${\mathcal {S}}$$ S -procedure. With the known transmit covariance matrix at the transmitter, the optimization problem is transformed into another SDP by converting the MSE minimization constraint into a linear matrix inequality. Simulation results have shown that our proposed robust transceiver design outperforms the non-robust one.
Wireless Personal Communications – Springer Journals
Published: Feb 9, 2017
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