Ergodic Rate of Reconfigurable Intelligent Surface-Assisted Multigroup Multicast System-Reference-Cited by-同舟云学术

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Ergodic Rate of Reconfigurable Intelligent Surface-Assisted Multigroup Multicast System

Published:2023-04 Issue:4 Volume:72 Page:5485-5490
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Chen Zhengchuan¹^ORCID,Chen Li¹,Tian Zhong¹^ORCID,Wang Min²^ORCID,Jia Yunjian¹^ORCID,Dai Linglong³^ORCID

Affiliation:

1. School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China

2. School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

3. Department of Electronic Engineering, Tsinghua University, Beijing, China

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

State Key Laboratory of Integrated Services Networks

Opening Fund of State Key Laboratory of Millimeter Waves

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/10104191/09983534.pdf?arnumber=9983534

Reference14 articles.

1. Joint Power and Subcarrier Allocation Optimization for Multigroup Multicast Systems With Rate Splitting

2. SWIPT in MISO Multicasting Systems

3. Intelligent Reflecting Surface Aided Multigroup Multicast MISO Communication Systems

4. User Selection in Reconfigurable Intelligent Surface Assisted Communication Systems

5. Performance Analysis of Reconfigurable Intelligent Surface-Assisted Wireless Systems and Comparison With Relaying

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sum-Rate Optimization Algorithms for RIS Aided D2D Multicast System Based on Hypergraph;IEEE Wireless Communications Letters;2024-05

2. Joint Beamforming for RIS-Assisted Multicast System Based on Model-Driven Deep Learning;2023 IEEE 23rd International Conference on Communication Technology (ICCT);2023-10-20

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