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IRS辅助C-IoT系统的保密率设计

孙振兴 胥子昂 南春萍 李雪峰 许红

计算机技术与发展2026,Vol.36Issue(2):10-15,6.
计算机技术与发展2026,Vol.36Issue(2):10-15,6.DOI:10.20165/j.cnki.ISSN1673-629X.2025.0248

IRS辅助C-IoT系统的保密率设计

Design of Secrecy Rate for IRS Assisted C-IoT System

孙振兴 1胥子昂 2南春萍 3李雪峰 2许红2

作者信息

  • 1. 东北石油大学秦皇岛校区 电气信息工程系,河北 秦皇岛 066004
  • 2. 东北石油大学 电气信息工程学院,黑龙江 大庆 163318
  • 3. 东北石油大学秦皇岛校区 基础部,河北 秦皇岛 066004
  • 折叠

摘要

Abstract

A secrecy rate optimization scheme based on joint beamforming is proposed for the C-IoT(Cognitive Internet of Things)communication system with eavesdroppers assisted by IRS(Intelligent Reflecting Surface).In the system model,a multiple-input single-output communication scenario consisting of a transmitter,a primary user,a secondary user,an eavesdropper,and an IRS is considered.Based on this model,the secrecy rate optimization problem is constructed.That is,under the constraints of the total transmit power of the transmitter,the interference power at the primary user side,and the unit modulus constraint of the IRS,the SR(Secrecy Rate)of the system is maximized by jointly optimizing the active and passive beamforming.In the process of implementation,since the formulaic problem is non-convex,the problem is decomposed into two sub-problems by an alternate optimization method:the optimization of the transmitter beamforming matrix and the IRS phase-shift matrix.For the matrix optimization of transmitter beamforming,SDR(Semidefinite Relaxation)method and SCA(Successive Convex Approximation)method are used.The phase shift matrix of IRS is op-timized by Dinkelbach and SCA.The simulation results show that in a MISO system with eavesdroppers,the introduction of IRS to optimize active and passive beamforming effectively improves the system's secrecy rate.

关键词

智能反射面/认知物联网/多输入单输出/波束成型/保密率

Key words

intelligent reflecting surface/cognitive internet of things/multiple input single output/beamforming/secrecy rate

分类

信息技术与安全科学

引用本文复制引用

孙振兴,胥子昂,南春萍,李雪峰,许红..IRS辅助C-IoT系统的保密率设计[J].计算机技术与发展,2026,36(2):10-15,6.

基金项目

黑龙江省自然科学基金项目(LH2022F004) (LH2022F004)

东北石油大学青年科学基金项目(2020QNQ-05) (2020QNQ-05)

计算机技术与发展

1673-629X

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