Reconfigurable intelligent surface assisted resource optimization method for heterogeneous network

Xianhao SHEN; Ziling ZENG; Shaohua NIU

doi:10.11959/j.issn.1000-436x.2022217

您当前的位置：

首页 >

文章列表页 >

Reconfigurable intelligent surface assisted resource optimization method for heterogeneous network

Papers | 更新时间：2024-06-05

- Reconfigurable intelligent surface assisted resource optimization method for heterogeneous network
- Journal on Communications Vol. 43, Issue 11, Pages: 171-182(2022)
- 作者机构：
  
  1. 桂林理工大学信息科学与工程学院，广西桂林 541006
  2. 桂林理工大学广西嵌入式技术与智能系统实验室，广西桂林 541006
  3. 北京理工大学机电学院，北京 100081
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62262011);The National Natural Science Foundation of China(61961010);Guangxi Natural Science Foundation(2020GXNSFAA297255)
- DOI：10.11959/j.issn.1000-436x.2022217
  CLC： TP302
- Online First：2022-11，
  
  Published：25 November 2022
- 稿件说明：
移动端阅览
Xianhao SHEN, Ziling ZENG, Shaohua NIU. Reconfigurable intelligent surface assisted resource optimization method for heterogeneous network[J]. Journal on Communications, 2022, 43(11): 171-182.
DOI：

Xianhao SHEN, Ziling ZENG, Shaohua NIU. Reconfigurable intelligent surface assisted resource optimization method for heterogeneous network[J]. Journal on Communications, 2022, 43(11): 171-182. DOI： 10.11959/j.issn.1000-436x.2022217.

摘要

针对可重构智能表面（RIS）辅助的异构网络切片，提出了联合资源分配和相移优化的资源优化方法。对于异构网络中的不同业务，构建了不同目标的联合优化问题。针对增强型移动宽带（eMBB）业务，基于交替优化算法，联合优化资源块分配、功率分配和RIS相移矩阵，使eMBB用户的遍历总容量最大化。针对超可靠低时延通信（URLLC）业务，以最大化 URLLC 数据包接收率和最小化 eMBB 速率损失为目标，提出基于预配置RIS的启发式URLLC分配算法。仿真结果表明，与未部署RIS时95.95%的URLLC数据包接收率相比，所提算法仅使用80个RIS，实现了约99.99%的URLLC数据包接收率，同时提高了约86.24%的eMBB速率总和。

Abstract

For reconfigurable intelligent surface (RIS)-assisted heterogeneous network slicing

a resource optimization method with joint resource allocation and phase shift optimization was proposed.A joint optimization problem with different objectives was constructed for different services in heterogeneous networks.For enhanced mobile broadband (eMBB) services

the resource block allocation

power allocation and RIS phase shift matrix were jointly optimized based on the alternating optimization algorithm to maximize the total traversal capacity of eMBB users.For ultra-reliable low-latency communication (URLLC) services

a pre-configured RIS-based heuristic URLLC allocation algorithm was proposed with the objectives of maximizing the URLLC packet reception rate and minimizing the amount of eMBB rate loss.Simulation results demonstrate that the proposed algorithm achieves about 99.99% URLLC packet reception rate using only 80 RISs compared to 95.95% URLLC packet reception rate when no RISs are deployed

while the total eMBB rate is increased by 86.24%.

关键词

Keywords

references

IMT-2020 (5G）推进组发布5G技术白皮书 [J ] . 中国无线电 , 2015 ( 5 ): 6

IMT-2020 (5G）Advancement group releases white paper on 5G technology [J ] . China Radio , 2015 ( 5 ): 6 .

PARK J , SAMARAKOON S , SHIRI H , et al . Extreme URLLC:vision,challenges,and key enablers [J ] . arXiv Preprint,arXiv:2001.09683 , 2020 .

POPOVSKI P , TRILLINGSGAARD K F , SIMEONE O , et al . 5G wireless network slicing for eMBB,URLLC,and mMTC:a communication-theoretic view [J ] . IEEE Access , 2018 , 6 : 55765 - 55779 .

ZHANG X F , GUO X D , ZHANG H . RB allocation scheme for eMBB and URLLC coexistence in 5G and beyond [J ] . Wireless Communications and Mobile Computing,2021 , 2021 :6644323.

王佳佳 , 陈琪美 , 江昊 . MIMO-NOMA系统下的URLLC与eMBB混合业务场景的共存调度研究 [J ] . 武汉大学学报(工学版) , 2021 ( 5 ): 1 - 8 .

WANG J J , CHEN Q M , JIANG H . Co-existence scheduling of URLLC and eMBB hybrid Service Scenarios in MIMO-NOMA System [J ] . Journal of Wuhan University (Engineering Edition) , 2021 ( 5 ): 1 - 8 .

BAIRAGI A K , MUNIR M S , ALSENWI M , et al . A matching based coexistence mechanism between eMBB and URLLC in 5G wireless networks [C ] // The 34th ACM/SIGAPP Symposium On Applied Computing . New York:ACM Press , 2019 : 2377 - 2384 .

BAIRAGI A K , MUNIR M S , ALSENWI M , et al . Coexistence mechanism between eMBB and URLLC in 5G wireless networks [J ] . IEEE Transactions on Communications , 2021 , 69 ( 3 ): 1736 - 1749 .

FU Y , WANG S , WANG C X , et al . Artificial Intelligence to Manage network traffic of 5G wireless networks [J ] . IEEE Network , 2018 , 32 ( 6 ): 58 - 64 .

HUANG Y , LI S R , LI C Z , et al . A deep-reinforcement-learning-based approach to dynamic eMBB/URLLC multiplexing in 5G NR [J ] . IEEE Internet of Things Journal , 2020 , 7 ( 7 ): 6439 - 6456 .

罗志强 , 王伟 , 朱晓荣 . 基于A3C的无线异构网络自适应视频流传输控制方法 [J ] . 电信科学 , 2020 , 36 ( 12 ): 65 - 76 .

LUO Z Q , WANG W , ZHU X R , et al . An adaptive video stream transmission control method for wireless heterogeneous networks based on A3C [J ] . Telecommunications Science , 2020 , 36 ( 12 ): 65 - 76 .

ALSENWI M , TRAN N H , BENNIS M , et al . Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond:a deep reinforcement learning based approach [J ] . IEEE Transactions on Wireless Communications , 2021 , 20 ( 7 ): 4585 - 4600 .

YOUN J , SON W , JUNG B C . Physical-layer security improvement with reconfigurable intelligent surfaces for 6G wireless communication systems [J ] . Sensors , 2021 , 21 ( 4 ): 1439 .

LIU Y W , LIU X , MU X D , et al . Reconfigurable intelligent surfaces:principles and opportunities [J ] . IEEE Communications Surveys ＆ Tutorials , 2021 , 23 ( 3 ): 1546 - 1577 .

WU Q Q , ZHANG R . Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming [J ] . IEEE Transactions on Wireless Communications , 2019 , 18 ( 11 ): 5394 - 5409 .

RANJHA A , KADDOUM G . URLLC facilitated by mobile UAV relay and RIS:a joint design of passive beamforming,blocklength,and UAV positioning [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 6 ): 4618 - 4627 .

MELGAREJO D C , KALALAS C , SENA A , et al . Reconfigurable intelligent surface-aided grant-free access for uplink URLLC [C ] // Proceedings of the 2nd 6G Wireless Summit . Piscataway:IEEE Press , 2020 : 1 - 5 .

GHANEM W R , JAMALI V , SCHOBER R . Joint beamforming and phase shift optimization for multicell IRS-aided OFDMA-URLLC systems [C ] // Proceedings of IEEE Wireless Communications and Networking Conference . Piscataway:IEEE Press , 2021 : 1 - 7 .

AL-MEKHLAFI M , ARFAOUI M A , ELHATTAB M , et al . Joint resource allocation and phase shift optimization for RIS-aided eMBB/URLLC traffic multiplexing [J ] . IEEE Transactions on Communications , 2022 , 70 ( 2 ): 1304 - 1319 .

KORRAI P , LAGUNAS E , SHARMA S K , et al . A RAN resource slicing mechanism for multiplexing of eMBB and URLLC services in OFDMA based 5G wireless networks [J ] . IEEE Access , 2020 , 8 : 45674 - 45688 .

PASTUSHOK I A , BOIKOV N A . Investigation of methods for multiplexing EMBB and URLLC streams in a downlink [C ] // Proceedings of Wave Electronics and its Application in Information and Telecommunication Systems (WECONF) . Piscataway:IEEE Press , 2019 : 1 - 4 .

GARCIA-ARMADA A . SNR gap approximation for M-PSK-Based bit loading [J ] . IEEE Transactions on Wireless Communications , 2006 , 5 ( 1 ): 57 - 60 .

BOYD S , VANDENBERFHE L . Convex optimization [M ] . Cambridge : Cambridge University Press , 2004 .

CHEN Y B , WANG Y , LIU M , et al . Network slicing enabled resource management for service-oriented ultra-reliable and low-latency vehicular networks [J ] . IEEE Transactions on Vehicular Technology , 2020 , 69 ( 7 ): 7847 - 7862 .

Views

949

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

RIS substructure-based direct localization algorithm with multipath suppression via compressed sensing

Review on the new antenna evolution for next generation Wi-Fi 7/8 systems

Research on boosting self-sustainability for RIS-aided multi-cluster wireless powered communication networks

Research on task offloading and resource allocation in edge computing network of RIS assisted UAV based on Lyapunov

Time-varying channel estimation in reconfigurable intelligent surface assisted communication system

Related Author

Li Jingjing

Wang Jianhui

Liu Lihao

Zhang Yanyu

Hu Nan

DONG Yuandan

YOU Jiawen

LI Tongbo

Related Institution

College of Information Systems Engineering, Information Engineering University

School of Electronic Science and Engineering, University of Electronic Science and Technology of China

Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China

Chongqing Key Laboratory of Mobile Communications Technology

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications

AI问答

⁰