基于并行CNN的RIS辅助D2D保密通信系统资源分配算法

朱政宇; 侯庚旺; 黄崇文; 孙钢灿; 郝万明; 梁静

doi:10.11959/j.issn.1000-436x.2022046

您当前的位置：

首页 >

文章列表页 >

基于并行CNN的RIS辅助D2D保密通信系统资源分配算法

学术论文 | 更新时间：2024-06-05

- 基于并行CNN的RIS辅助D2D保密通信系统资源分配算法
- Systems resource allocation algorithm for RIS-assisted D2D secure communication based on parallel CNN
- 通信学报 2022年43卷第3期页码：172-179
- 作者机构：
  
  1. 郑州大学信息工程学院，河南郑州 450001
  2. 郑州大学电子材料与系统国际联合研究中心，河南郑州 450001
  3. 浙江大学信息与电子工程学院，浙江杭州 310027
  4. 郑州大学电气工程学院，河南郑州 450001
- 作者简介：
  
  [ "朱政宇（1988- ），男，河南鹿邑人，博士，郑州大学副教授，主要研究方向为智能反射面技术、物理层安全技术、无线通信与信号处理等" ]
  [ "侯庚旺（1996- ），男，河南林州人，郑州大学硕士生，主要研究方向为物理层安全技术与机器学习" ]
  [ "黄崇文（1986- ），男，浙江杭州人，博士，浙江大学研究员，主要研究方向为智能超表面、深度学习、B5G/6G 通信等" ]
  [ "孙钢灿（1977- ），男，河南濮阳人，博士，郑州大学教授，主要研究方向为深度学习、机器学习、无线通信、物理层安全技术等" ]
  [ "郝万明（1988- ），男，河南林州人，博士，郑州大学副研究员，主要研究方向为毫米波通信、大规模 MIMO 技术、物理层安全技术等" ]
  [ "梁静（1981- ），女，河南兰考人，博士，郑州大学教授，主要研究方向为计算智能、智能优化及机器学习等" ]
- 基金信息：
  
  国家自然科学基金资助项目(61922072);国家自然科学基金资助项目(62101499);国家自然科学基金资助项目(62101492);国家重点研发计划基金资助项目(2019QY0302);国家重点研发计划基金资助项目(2019YFB1803200);国家重点研发计划基金资助项目(2021YFA1000500);中国博士后科学基金资助项目(2020M682345);河南省博士后经费资助项目(202001015);郑州市重大科技创新专项基金资助项目(2019CXZX0037);浙江省自然科学基金资助项目(LR22F010002)
- DOI：10.11959/j.issn.1000-436x.2022046
  中图分类号： TN92
- 网络出版日期：2022-03，
  
  纸质出版日期：2022-03-25
- 稿件说明：
移动端阅览
朱政宇, 侯庚旺, 黄崇文, 等. 基于并行CNN的RIS辅助D2D保密通信系统资源分配算法[J]. 通信学报, 2022,43(3):172-179.

Zhengyu ZHU, Gengwang HOU, Chongwen HUANG, et al. Systems resource allocation algorithm for RIS-assisted D2D secure communication based on parallel CNN[J]. Journal on communications, 2022, 43(3): 172-179.
朱政宇, 侯庚旺, 黄崇文, 等. 基于并行CNN的RIS辅助D2D保密通信系统资源分配算法[J]. 通信学报, 2022,43(3):172-179. DOI： 10.11959/j.issn.1000-436x.2022046.

Zhengyu ZHU, Gengwang HOU, Chongwen HUANG, et al. Systems resource allocation algorithm for RIS-assisted D2D secure communication based on parallel CNN[J]. Journal on communications, 2022, 43(3): 172-179. DOI： 10.11959/j.issn.1000-436x.2022046.

摘要

为满足智能信号处理和物理层安全需求，针对频谱资源紧缺问题，提出了一种智能超表面辅助设备到设备（D2D）通信的资源分配算法。D2D 用户通过复用蜂窝用户频谱资源实现通信，考虑 D2D 传输速率、基站发射功率和RIS发射相移约束，构建了用户保密速率最大化问题。为了解决该非线性规划问题，提出了一种并行卷积神经网络算法，以得到最佳资源分配方案。仿真结果表明，所提算法能够有效提高系统保密速率，且明显优于其他基准算法。

Abstract

To meet the requirements of intelligent signal processing and physical layer security

aiming at the shortage of spectrum resources

a resource allocation algorithm for reconfigurable intelligent surface (RIS)-assisted the device to device (D2D) communication was proposed.D2D users communicated by multiplexing the spectrum resources of cellular users.Considering the constraints of D2D transmission rate

base station transmission power and RIS transmission phase shift

the problem of maximizing user security rate was formulated.To solve the nonlinear programming problem

a parallel convolutional neural network (CNN) algorithm was proposed to obtain the optimal resource allocation scheme.Simulation results show that the parallel CNN algorithm can effectively improve the secrecy rate and it is significantly better than other benchmark algorithms.

关键词

Keywords

references

LIU S H , WU Y C , LI L , et al . A two-stage energy-efficient approach for joint power control and channel allocation in D2D communication [J ] . IEEE Access , 2019 , 7 : 16940 - 16951 .

HUANG C W , HU S , ALEXANDROPOULOS G C , et al . Holographic MIMO surfaces for 6G wireless networks:opportunities,challenges,and trends [J ] . IEEE Wireless Communications , 2020 , 27 ( 5 ): 118 - 125 .

XU Y J , LIU Z J , HUANG C W , et al . Robust resource allocation algorithm for energy-harvesting-based D2D communication underlaying UAV-assisted networks [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 23 ): 17161 - 17171 .

HOANG T D , LE L B , LE-NGOC T , . Joint mode selection and resource allocation for relay-based D2D communications [J ] . IEEE Communications Letters , 2017 , 21 ( 2 ): 398 - 401 .

GAO H Y , ZHANG S B , SU Y M , et al . Joint resource allocation and power control algorithm for cooperative D2D heterogeneous networks [J ] . IEEE Access , 2019 , 7 : 20632 - 20643 .

钱志鸿 , 田春生 , 王鑫 , 等 . D2D 网络中信道选择与功率控制策略研究 [J ] . 电子与信息学报 , 2019 , 41 ( 10 ): 2287 - 2293 .

QIAN Z H , TIAN C S , WANG X , et al . Research on channel selection and power control strategy for D2D networks [J ] . Journal of Electronics ＆ Information Technology , 2019 , 41 ( 10 ): 2287 - 2293 .

NIU H H , CHU Z , ZHOU F H , et al . Weighted sum secrecy rate maximization using intelligent reflecting surface [J ] . IEEE Transactions on Communications , 2021 , 69 ( 9 ): 6170 - 6184 .

XU Y J , GAO Z N , WANG Z Q , et al . RIS-enhanced WPCNs:joint radio resource allocation and passive beamforming optimization [J ] . IEEE Transactions on Vehicular Technology , 2021 , 70 ( 8 ): 7980 - 7991 .

ZHANG C Y , CHEN W Y , HE C L , et al . Throughput maximization for intelligent reflecting surface-aided device-to-device communications system [J ] . Journal of Communications and Information Networks , 2020 , 5 ( 4 ): 403 - 410 .

朱政宇 , 王梓晅 , 徐金雷 , 等 . 智能反射面辅助的未来无线通信:现状与展望 [J ] . 航空学报 , 2021 ,doi:10.7527/S1000- 6893.2021.25014.

ZHU Z Z , WANG Z X , XU J L , et al . Future wireless communication assisted by intelligent reflecting surface:current situation and prospect [J ] . Journal of Aeronautics 2021 ,doi:10.7527/S1000- 6893.2021.25014.

朱政宇 , 徐金雷 , 孙钢灿 , 等 . 基于IRS辅助的SWIPT物联网系统安全波束成形设计 [J ] . 通信学报 , 2021 , 42 ( 4 ): 185 - 193 .

ZHU Z Y , XU J L , SUN G C , et al . Secure beamforming design for IRS-assisted SWIPT Internet of things system [J ] . Journal on Communications , 2021 , 42 ( 4 ): 185 - 193 .

ZHU Z Y , LI Z , CHU Z , et al . Resource allocation for intelligent reflecting surface assisted wireless powered IoT systems with power splitting [J ] . IEEE Transactions on Wireless Communications , 2021 , 14 ( 12 ): 363 .

LIU M , SONG T C , HU J , et al . Deep learning-inspired message passing algorithm for efficient resource allocation in cognitive radio networks [J ] . IEEE Transactions on Vehicular Technology , 2019 , 68 ( 1 ): 641 - 653 .

ZHU Z Y , XU J L , SUN G C , et al . Robust beamforming design for IRS-aided secure SWIPT terahertz systems with non-linear EH model [J ] . IEEE Wireless Communications Letters , 2022 , PP ( 99 ): 1 .

陈前斌 , 管令进 , 李子煜 , 等 . 基于深度强化学习的异构云无线接入网自适应无线资源分配算法 [J ] . 电子与信息学报 , 2020 , 42 ( 6 ): 1468 - 1477 .

CHEN Q B , GUAN L J , LI Z Y , et al . Deep reinforcement learning-based adaptive wireless resource allocation algorithm for heterogeneous cloud wireless access network [J ] . Journal of Electronics ＆Information Technology , 2020 , 42 ( 6 ): 1468 - 1477 .

GUI G , HUANG H J , SONG Y W , et al . Deep learning for an effective nonorthogonal multiple access scheme [J ] . IEEE Transactions on Vehicular Technology , 2018 , 67 ( 9 ): 8440 - 8450 .

KIM J , PARK J , NOH J , et al . Autonomous power allocation based on distributed deep learning for device-to-device communication underlaying cellular network [J ] . IEEE Access , 2020 , 8 : 107853 - 107864 .

LIU X . Optimisation of the duplex D2D network:a deep learning approach [J ] . IET Networks , 2020 , 9 ( 3 ): 139 - 144 .

ÖZBEK B , PISCHELLA M , LE R D . Energy efficient resource allocation for underlaying multi-D2D enabled multiple-antennas communications [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 6 ): 6189 - 6199 .

NGUYEN K K , DUONG T Q , VIEN N A , et al . Non-cooperative energy efficient power allocation game in D2D communication:a multi-agent deep reinforcement learning approach [J ] . IEEE Access , 2019 , 7 : 100480 - 100490 .

JACOB S , MENON V G , JOSEPH S , et al . A novel spectrum sharing scheme using dynamic long short-term memory with CP-OFDMA in 5G networks [J ] . IEEE Transactions on Cognitive Communications and Networking , 2020 , 6 ( 3 ): 926 - 934 .

HUANG C W , YANG Z H , ALEXANDROPOULOS G C , et al . Multi-hop RIS-empowered terahertz communications:a DRL-based hybrid beamforming design [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 6 ): 1663 - 1677 .

LEE J , LEE J H . Performance analysis and resource allocation for cooperative D2D communication in cellular networks with multiple D2D pairs [J ] . IEEE Communications Letters , 2019 , 23 ( 5 ): 909 - 912 .

JIANG L , QIN C , ZHANG X X , et al . Secure beamforming design for SWIPT in cooperative D2D communications [J ] . China Communications , 2017 , 14 ( 1 ): 20 - 33 .

YANG B , CAO X L , HUANG C W , et al . Intelligent spectrum learning for wireless networks with reconfigurable intelligent surfaces [J ] . IEEE Transactions on Vehicular Technology , 2021 , 70 ( 4 ): 3920 - 3925 .

LI D , QIAO D L , ZHANG L , et al . Performance analysis of indoor THz communications with one-bit precoding [C ] // Proceedings of 2018 IEEE Global Communications Conference . Piscataway:IEEE Press , 2018 : 1 - 7 .

WADAYAMA T . Interior point decoding for linear vector channels based on convex optimization [J ] . IEEE Transactions on Information Theory , 2010 , 56 ( 10 ): 4905 - 4921 .

BUDHIRAJA I , KUMAR N , TYAGI S . Deep-reinforcement-learningbased proportional fair scheduling control scheme for underlay D2D communication [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 5 ): 3143 - 3156 .

LIN B , WANG X D , YUAN W H , et al . A novel OFDM autoencoder featuring CNN-based channel estimation for Internet of vessels [J ] . IEEE Internet of Things Journal , 2020 , 7 ( 8 ): 7601 - 7611 .

浏览量

505

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

无人机辅助D2D通信网络安全通信资源分配算法

D2D通信的干扰控制和资源分配算法研究

基于神经网络的恶意DNS流量检测方法

基于耦合相移STAR-RIS的认知无线电系统资源分配算法

基于同态密文转换的隐私保护卷积神经网络推理方案