Manifold Optimization Algorithms for SWIPT over MIMO Broadcast Channels with Discrete Input Signals
Abstract
In this paper, the design of linear precoders for simultaneously wireless information and power transfer (SWIPT) over multi-input multi-output (MIMO) broadcast channels with discrete input signals is investigated. The considered system model consists of one base station (BS), one information receiver (IR) and one energy receiver (ER). The design objective is to maximize the input-output mutual information of the IR subject to the harvested energy requirement for the ER. The structure of the optimal precoder is derived by using the methods of manifold optimization, and an algorithm is proposed to find the optimal precoder. Simulation results show that the proposed algorithm can achieve better performance than the time sharing scheme and the optimal precoder designed for Gaussian inputs.
Recommended Citation
A. Lu et al., "Manifold Optimization Algorithms for SWIPT over MIMO Broadcast Channels with Discrete Input Signals," Proceedings of the 2017 IEEE International Conference on Communications (2017, Paris, France), Institute of Electrical and Electronics Engineers (IEEE), May 2017.
The definitive version is available at https://doi.org/10.1109/ICC.2017.7997006
Meeting Name
2017 IEEE International Conference on Communications, ICC (2017: May 21-25, Paris, France)
Department(s)
Electrical and Computer Engineering
Sponsor(s)
National Natural Science Foundation (China)
Ministry of Science and Technology of the People's Republic of China. 863 Program
National Science and Technology Major Project of China
Huawei Cooperation Project
National Science Foundation (U.S.)
Keywords and Phrases
Manifold optimization; MIMO; Precoder; SWIPT
International Standard Book Number (ISBN)
978-1-4673-8999-0
International Standard Serial Number (ISSN)
1550-3607; 1938-1883
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 May 2017
Comments
The work of A.-A. Lu and X. Q. Gao was supported in part by National Natural Science Foundation of China under Grants 61320106003, 61471113, 61521061 and 61631018, the China High-Tech 863 Plan under Grants 2015AA01A701 and 2014AA01A704, National Science and Technology Major Project of China under Grant 2014ZX03003006-003, and the Huawei Cooperation Project. The work of Y. R. Zheng and C. Xiao was supported in part by USA National Science Foundation under Grants ECCS-1231848, ECCS-1408316 and ECCS-1539316.