Achievable rates in IRS-assisted NOMA-enabled IoT systems under channel estimation errors

Widad Belaoura, Zineb Yamoutene, Muhammad Zeeshan Shakir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Intelligent Reflecting Surface (IRS) represents a revolutionary technology for effectively enhancing the performance of Internet-of-Things (IoT) networks owing to its ability of customizing the wireless propagation environment and compatibility with advanced communication techniques, such as non-orthogonal multiple-access (NOMA). This paper investigates the impact of imperfect channel state information (CSI) on the achievable data rate of IRS-Aided downlink NOMA-enabled IoT framework over Rician fading channels. Specifically, the imperfect CSI is considered from the IRS to the IoT devices. The results demonstrated that imperfect CSI has a significant impact on the achievable rate performance of the far and near IoT devices, which are also different under different numbers of reflecting units.
Original languageEnglish
Title of host publication2024 2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC
PublisherIEEE
Publication statusAccepted/In press - 1 Mar 2024

Keywords

  • intelligent reflecting surface (IRS)
  • 6G
  • NOMA
  • imperfect CSI
  • internet-of-things (IoT)
  • achievable rate

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