Secrecy Rate Optimization in NonLinear Energy Harvesting Model-Based mmWave IoT Systems With SWIPT

Zhengyu Zhu, Mengyuan Ma, Gangcan Sun, Wanming Hao, Peijia Liu, Zheng Chu, Inkyu Lee

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
JournalIEEE Systems Journal
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Channel state information (CSI)
  • Electronic mail
  • Internet of Things
  • Internet of Things (IoT)
  • millimeter wave (mmWave)
  • MIMO communication
  • nonlinear energy harvesting (EH) model
  • Optimization
  • Precoding
  • Radio frequency
  • Receivers
  • simultaneous wireless information and power transfer (SWIPT)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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