Deep Non-Orthogonal Multiple Access Network Assisted by Intelligent Reflecting Surface

Authors

  • Dahua Ouyang Hainan Normal University
  • Pingzhi Shangguan Hainan Normal University
  • Xinyong Huangfu Hainan Normal University
  • Zenggang Linghu Hainan Normal University
  • Haiyang Zhuge Dalian Jiaotong University
  • Haoliang Situ Dalian Jiaotong University
  • Shangwu Sima Dalian Jiaotong University
  • Junning Shentu Dalian Jiaotong University
  • Yuanrui Xiahou Southwest Forestry University
  • Zhengtao Helan Southwest Forestry University
  • Zhaoyao Dongfang Southwest Forestry University
  • Kunlun Dongfang Southwest Forestry University
  • Zhengzhi Wanyan Yanbian University
  • Qingrong Murong Yanbian University
  • Hanming Yuchi Yanbian University
  • Zhongchun Zhangsun Yanbian University
  • Bingyun Helan Jishou University
  • Haida Xiahou Jishou University
  • Yifan Shentu Jishou University
  • Weiye Sima Jishou University
  • Zhengfeng Situ Yunnan Normal University
  • Fengqi Zhuge Yunnan Normal University
  • Jiayi Linghu Yunnan Normal University
  • Zhili Huangpu Yunnan Normal University
  • Weiyi Shangguan Shanghai Maritime University
  • Shanshan Ouyang Shanghai Maritime University
  • Xiatian Ouyang Shanghai Maritime University
  • Zhimo Shangguan Shanghai Maritime University
  • Dechang Huangpu Jiangsu Normal University
  • Bozhong Linghu Jiangsu Normal University
  • Houjue Zhuge Jiangsu Normal University
  • Yunfei Situ Jiangsu Normal University
  • Bobo Sima Hubei University of Technology
  • Zelong Shentu Hubei University of Technology
  • Kunlun Xiahou Hubei University of Technology
  • Zhaohui Helan Hubei University of Technology
  • Siyu Wanyan Hubei University of Technology
  • Desheng Murong Chengdu University of Technology
  • Yingxiong Yunchi Chengdu University of Technology
  • Baoqiang Zhangsun Chengdu University of Technology
  • Jinshang Dongfang Chengdu University of Technology
  • Xiazhi Lai Chengdu University of Technology
  • Yinghao Guo Chengdu University of Technology
  • Bowen Lu Shantou University

DOI:

https://doi.org/10.4108/eetmca.v7i3.2750

Keywords:

IRS, NOMA, B5G

Abstract

The intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) symbiotic communication technology is expected to enhance the access performance, energy efficiency and spectrum efficiency of the communication network, and is regarded as an important candidate technology to support the evolution of the sixth-generation (6G) towards large-scale, high-capacity and sustainable development. However, the relevant research of this technology is still at the initial stage, and many key challenges have not been fully studied. Therefore, it is urgent to open up relevant research ideas and methods to promote its development and early implementation, so as to make it an effective 6G technology. In view of this, this paper intends to carry out the research on the theory and method of IRS assisted NOMA symbiotic transmission, starting from the analysis of the active and passive symbiotic mechanism of NOMA transmission protocol. Based on this, we further study the efficient symbiotic modulation transmission technology and multi-dimensional resource optimization allocation method. The research content of this paper is to explore the transmission theory and technology of high energy efficiency and high frequency spectrum efficiency for 6G, and break through the bottleneck problem of spectrum and energy consumption encountered by wireless communication, which has important practical significance for the wireless communication.

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Published

11-01-2023

How to Cite

1.
Ouyang D, Shangguan P, Huangfu X, Linghu Z, Zhuge H, Situ H, et al. Deep Non-Orthogonal Multiple Access Network Assisted by Intelligent Reflecting Surface. EAI Endorsed Trans Mob Com Appl [Internet]. 2023 Jan. 11 [cited 2025 Nov. 22];7(3):e4. Available from: https://publications.eai.eu/index.php/mca/article/view/2750

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