Fluid Reconfigurable Intelligent Surface Enabling Index Modulation

TL;DR

This paper introduces a novel fluid reconfigurable intelligent surface (FRIS) framework for index modulation, exploiting spatial degrees of freedom for improved communication performance with reduced detection complexity.

Contribution

It proposes a new FRIS-based index modulation framework and develops two transmission schemes, along with a low-complexity detector and comprehensive performance analysis under fading conditions.

Findings

Significant BER improvements over conventional RIS schemes

Accurate analytical expressions for error probability and BER

Validation of analysis through simulations

Abstract

Fluid reconfigurable intelligent surfaces (FRIS) enable joint position and phase reconfigurability by integrating fluid antennas (FA) with conventional reconfigurable intelligent surfaces (RIS). In this paper, we propose a novel FRIS-based index modulation (IM) framework that exploits the additional spatial degrees of freedom introduced by FRIS element-position reconfiguration. Based on this framework, two transmission schemes are developed, namely FRIS-assisted receiver spatial modulation (FRIS-RSM) and receiver spatial shift keying (FRIS-RSSK), where information bits are conveyed through receiver-antenna index selection. The proposed framework supports both continuous and finite-bit phase control while accounting for FRIS-side spatial correlation. To balance detection complexity and bit error rate (BER) performance, a two-stage reduced-complexity list detector is proposed. For performance analysis under double-Rayleigh cascaded fading with strongest-link selection, tractable post-selection statistics are developed for both continuous-phase and quantized-phase FRIS and incorporated into a moment-generating-function (MGF)-based framework to derive unconditional pairwise error probability (UPEP) and union-bound BER expressions. Simulation results demonstrate significant BER gains over conventional RIS-assisted schemes and verify the accuracy of the analysis.