TY - GEN
T1 - Robust Max-Min Fair Beamforming of Secrecy SWIPT IoT Systems under a Non-Linear EH Model
AU - Zhu, Zhengyu
AU - Wang, Zixuan
AU - Lin, Yu
AU - Liu, Peijia
AU - Hao, Wanming
AU - Wang, Zhongyong
AU - Lee, Inkyu
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61801434, 61801435 and 61771431, in part by the Science and Technology Innovation Project of Zhengzhou under Grant 2019CXZX0037, in part by the National Key Research and Development Program of China under Grant 2019YFB1803200, in part by the National Research Foundation (NRF) through the Ministry of Science, ICT, and Future Planning (MSIP), Korea Government under Grant 2017R1A2B3012316. Corresponding Author: Peijia Liu.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - In this paper, we study a robust beamforming design for multi-user multiple-input multiple-output secrecy networks with simultaneous wireless information and power transfer (SWIPT). In this system, an access point, multiple Internet of Things devices under the non-Linear energy harvesting model with a help of one cooperative jammer (CJ). We employ artificial noise (AN) generation to facilitate efficient wireless energy transfer and secure transmission. To achieve energy harvesting fairness, we aim to maximize the minimum harvested energy among users subject to secrecy rate constraint and total transmit power constraint in the presence of channel estimation errors. By incorporating a norm-bounded channel uncertainty model, we propose an algorithm based on sequential parametric convex approximation (SPCA). Finally, simulation results show that the proposed SPCA method outperforms the traditional AN-aided method and CJ-aided method.
AB - In this paper, we study a robust beamforming design for multi-user multiple-input multiple-output secrecy networks with simultaneous wireless information and power transfer (SWIPT). In this system, an access point, multiple Internet of Things devices under the non-Linear energy harvesting model with a help of one cooperative jammer (CJ). We employ artificial noise (AN) generation to facilitate efficient wireless energy transfer and secure transmission. To achieve energy harvesting fairness, we aim to maximize the minimum harvested energy among users subject to secrecy rate constraint and total transmit power constraint in the presence of channel estimation errors. By incorporating a norm-bounded channel uncertainty model, we propose an algorithm based on sequential parametric convex approximation (SPCA). Finally, simulation results show that the proposed SPCA method outperforms the traditional AN-aided method and CJ-aided method.
KW - CJ
KW - non-Linear energy harvesting
KW - norm-bounded channel uncertainty model
KW - SPCA
KW - SWIPT
UR - http://www.scopus.com/inward/record.url?scp=85112839192&partnerID=8YFLogxK
U2 - 10.1109/ICCWorkshops50388.2021.9473656
DO - 10.1109/ICCWorkshops50388.2021.9473656
M3 - Conference contribution
AN - SCOPUS:85112839192
T3 - 2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Proceedings
BT - 2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021
Y2 - 14 June 2021 through 23 June 2021
ER -