Robust Beamforming Design for RIS-Aided NOMA Networks With Imperfect Channels

Fengming Yang, Jianxin Dai, Cunhua Pan, Sheng Hong, Hong Ren, Kezhi Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

This paper studies the worst-case robust beamforming design for a reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) network with imperfect channels. We aim to minimize the transmission power while satisfying the requirement of the worst-case quality of service (QoS). With the worst-case QoS constraints, unit-modulus constraints and imperfect channel state information (CSI), this problem is a non-convex optimization problem. To solve this problem, we propose a two-procedure algorithm by applying penalty function and semidefinite relaxation (SDR). Finally, simulation results illustrate that the RIS-aided NOMA system has better performance than the traditional NOMA system.

Original languageEnglish
Title of host publication2022 IEEE 95th Vehicular Technology Conference
Subtitle of host publicationVTC2022-Spring
Place of PublicationPiscataway, US
ISBN (Electronic)9781665482431
DOIs
Publication statusPublished - Jun 2022

Publication series

NameIEEE Vehicular Technology Conference
Volume2022-June
ISSN (Print)1550-2252

Keywords

  • IRS
  • NOMA
  • RIS
  • imperfect CSI
  • robust beamforming

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