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Understanding the Role of Phase and Position Design in Fluid Reconfigurable Intelligent Surfaces

  • Jose David Vega Sanchez
  • , Victor Hugo Garzon Pacheco*
  • , Nathaly Veronica Orozco Garzon
  • , Henry Ramiro Carvajal Mora
  • , F. Javier Lopez-Martinez
  • *Corresponding author for this work
  • Universidad de las Americas - Ecuador
  • Universidad San Francisco de Quito
  • University of Granada

Research output: Contribution to journalArticlepeer-review

Abstract

Fluid Reconfigurable Intelligent Surfaces (FRISs) are gaining momentum as an improved alternative over classical RIS. However, it remains unclear whether their performance gains can be entirely attributed to spatial flexibility, or instead to differences in equivalent aperture or phase design. In this work, we shed light onto this problem by benchmarking FRIS vs. RIS performances in two practical scenarios: conventional RIS (same number of active elements and same overall aperture) and compact RIS (same number of active elements, and smaller aperture with sub-λ inter-element spacing). Statistical analysis demonstrates that: 1) spatial position optimization in FRIS provides noticeable gains over conventional RIS in the absence of phase-shift (PS) design; 2) such benefits vanish when FRIS and conventional RIS employ optimal beamforming (BF) and PS design, making position optimization irrelevant; and 3) FRIS consistently outperforms compact RIS with optimized BF and PS design, owing to spatial correlation and smaller aperture.

Original languageEnglish
Pages (from-to)1414-1425
Number of pages12
JournalIEEE Open Journal of the Communications Society
Volume7
DOIs
StatePublished - 2026

Keywords

  • Fluid reconfigurable intelligent surfaces (FRIS)
  • evolutionary particle swarm optimization (E-PSO)
  • outage probability (OP)
  • reconfigurable intelligent surfaces (RIS)
  • unsupervised learning

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