TY - JOUR
T1 - Secrecy Rate Optimization in Nonlinear Energy Harvesting Model-Based mmWave IoT Systems With SWIPT
AU - Zhu, Zhengyu
AU - Ma, Mengyuan
AU - Sun, Gangcan
AU - Hao, Wanming
AU - Liu, Peijia
AU - Chu, Zheng
AU - Lee, Inkyu
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61801434 and Grant 62101499, in part by the Project funded by China Postdoctoral Science Foundation under Grant 2020M682345, in part by the Henan Postdoctoral Foundation under Grant 202001015, in part by the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), Korea Government under Grant 2017R1A2B3012316.
Publisher Copyright:
© 2007-2012 IEEE.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Secrecy rate (SR) optimization in millimeter wave (mmWave) Internet of Things (IoT) systems with simultaneous wireless information and power transfer (SWIPT) is studied in this article. Adopting the SWIPT architecture, energy-constrained devices get charged by the radio-frequency waves transmitted from a base station. The hybrid precoding technique is applied to reduce the implementation cost by separately designing a digital precoder and an analog precoder. Also, we adopt the artificial noise (AN)-assisted transmission method to maximize the SR. In this problem, we aim to jointly optimize the digital precoding vector, AN covariance matrix, and power-splitting ratio under the nonlinear energy harvesting (EH)-constraints. Then, we propose a semidefinite relaxation-based alternating optimization algorithm for the case of perfect channel state information (CSI) and imperfect CSI. Finally, simulation results show that the proposed algorithms are effective to improve the SR.
AB - Secrecy rate (SR) optimization in millimeter wave (mmWave) Internet of Things (IoT) systems with simultaneous wireless information and power transfer (SWIPT) is studied in this article. Adopting the SWIPT architecture, energy-constrained devices get charged by the radio-frequency waves transmitted from a base station. The hybrid precoding technique is applied to reduce the implementation cost by separately designing a digital precoder and an analog precoder. Also, we adopt the artificial noise (AN)-assisted transmission method to maximize the SR. In this problem, we aim to jointly optimize the digital precoding vector, AN covariance matrix, and power-splitting ratio under the nonlinear energy harvesting (EH)-constraints. Then, we propose a semidefinite relaxation-based alternating optimization algorithm for the case of perfect channel state information (CSI) and imperfect CSI. Finally, simulation results show that the proposed algorithms are effective to improve the SR.
KW - Channel state information (CSI)
KW - Internet of Things (IoT)
KW - millimeter wave (mmWave)
KW - nonlinear energy harvesting (EH) model
KW - simultaneous wireless information and power transfer (SWIPT)
UR - http://www.scopus.com/inward/record.url?scp=85126563704&partnerID=8YFLogxK
U2 - 10.1109/JSYST.2022.3147889
DO - 10.1109/JSYST.2022.3147889
M3 - Article
AN - SCOPUS:85126563704
SN - 1932-8184
VL - 16
SP - 5939
EP - 5949
JO - IEEE Systems Journal
JF - IEEE Systems Journal
IS - 4
ER -