Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey

By Shimin Gong, Xiao Lu, Dinh Thai Hoang, Dusist Niyato, Lei Shu, Dong In Kim, Ying-Chang Liang. IEEE Communications Surveys and Tutorials, 2019

908 citations recorded by the source corpus.

This paper presents a literature review on recent applications and design aspects of the intelligent reflecting surface (IRS) in the future wireless networks. Conventionally, the network optimization has been limited to transmission control at two endpoints, i.e., end users and network controller. The fading wireless channel is uncontrollable and becomes one of the main limiting factors for performance improvement. The IRS is composed of a large array of scattering elements, which can be individually configured to generate additional phase shifts to the signal reflections. Hence, it can actively control the signal propagation properties in favor of signal reception, and thus realize the notion of a smart radio environment. As such, the IRS’s phase control, combined with the conventional transmission control, can potentially bring performance gain compared to wireless networks without IRS. In this survey, we first introduce basic concepts of the IRS and the realizations of its reconfigurability. Then, we focus on applications of the IRS in wireless communications. We overview different performance metrics and analytical approaches to characterize the performance improvement of IRS-assisted wireless networks. To exploit the performance gain, we discuss the joint optimization of the IRS’s phase control and the transceivers’ transmission control in different network design problems, e.g., rate maximization and power minimization problems. Furthermore, we extend the discussion of IRS-assisted wireless networks to some emerging use cases. Finally, we highlight important practical challenges and future research directions for realizing IRS-assisted wireless networks in beyond 5G communications.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/fb7ced0a032b059a3158074182f5bde1c5ff9702

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In Aerospace Engineering

  1. Yuanwei Liu
  2. M. Di Renzo
  3. Mohamed-Slim Alouini
  4. Merouane Debbah
  5. Chau Yuen
  6. Xidong Mu
  7. Naofal Al-Dhahir
  8. Rui Zhang

In Electrical and Electronic Engineering

  1. Yuanwei Liu
  2. Merouane Debbah
  3. Xidong Mu
  4. M. Di Renzo
  5. Mohamed-Slim Alouini
  6. Chau Yuen
  7. Naofal Al-Dhahir
  8. Alessio Zappone

In Ocean Engineering

  1. Naofal Al-Dhahir
  2. Mohamed-Slim Alouini
  3. Merouane Debbah
  4. Chau Yuen
  5. M. Di Renzo
  6. Jiaqi Xu
  7. Xiao Liu
  8. Yuanwei Liu

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