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FIRES: Fluid Integrated Reflecting and Emitting Surfaces

Farshad Rostami Ghadi, Kai-Kit Wong, Masoud Kaveh, F. Javier Lopez-Martinez, Chan-Byoung Chae, George C. Alexandropoulos

TL;DR

This work introduces FIRES, a fluid-integrated reflecting and emitting surface that merges STAR-RIS dual-mode functionality with dynamic repositioning of fluid metasurface elements. It formulates an effective-rate maximization problem under the energy-splitting protocol, optimizing element positions, mode coefficients, and phase shifts, and solves it with a customized particle swarm optimization algorithm where the objective includes penalties for spacing and power constraints. Simulations demonstrate that FIRES significantly outperforms conventional STAR-RIS in multicast downlink scenarios, achieving higher spectral efficiency by leveraging both electromagnetic and spatial reconfigurability; gains grow with larger surface area and higher element density, albeit with eventual saturation. Overall, FIRES offers a highly adaptable metasurface architecture with strong potential to enhance connectivity, spatial reuse, and energy efficiency in next-generation wireless networks, particularly under dynamic propagation conditions.

Abstract

This letter introduces the concept of fluid integrated reflecting and emitting surface (FIRES), which constitutes a new paradigm seamlessly integrating the flexibility of fluid-antenna systems (FASs) with the dual functionality of simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs). The potential of the proposed metasurface structure is studied though an FIRES-enabled multicast system based on the energy splitting protocol. In this model, the FIRES is divided into non-overlapping subareas, each functioning as a 'fluid' element capable of concurrent reflection and transmission and changing its position of radiation within the subarea. In particular, we formulate an optimization problem for the design of the triple tunable features of the surface unit elements, which is solved via a tailored particle swarm optimization approach. Our results showcase that the proposed FIRES architecture significantly outperforms its conventional STAR-RIS counterpart.

FIRES: Fluid Integrated Reflecting and Emitting Surfaces

TL;DR

This work introduces FIRES, a fluid-integrated reflecting and emitting surface that merges STAR-RIS dual-mode functionality with dynamic repositioning of fluid metasurface elements. It formulates an effective-rate maximization problem under the energy-splitting protocol, optimizing element positions, mode coefficients, and phase shifts, and solves it with a customized particle swarm optimization algorithm where the objective includes penalties for spacing and power constraints. Simulations demonstrate that FIRES significantly outperforms conventional STAR-RIS in multicast downlink scenarios, achieving higher spectral efficiency by leveraging both electromagnetic and spatial reconfigurability; gains grow with larger surface area and higher element density, albeit with eventual saturation. Overall, FIRES offers a highly adaptable metasurface architecture with strong potential to enhance connectivity, spatial reuse, and energy efficiency in next-generation wireless networks, particularly under dynamic propagation conditions.

Abstract

This letter introduces the concept of fluid integrated reflecting and emitting surface (FIRES), which constitutes a new paradigm seamlessly integrating the flexibility of fluid-antenna systems (FASs) with the dual functionality of simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs). The potential of the proposed metasurface structure is studied though an FIRES-enabled multicast system based on the energy splitting protocol. In this model, the FIRES is divided into non-overlapping subareas, each functioning as a 'fluid' element capable of concurrent reflection and transmission and changing its position of radiation within the subarea. In particular, we formulate an optimization problem for the design of the triple tunable features of the surface unit elements, which is solved via a tailored particle swarm optimization approach. Our results showcase that the proposed FIRES architecture significantly outperforms its conventional STAR-RIS counterpart.
Paper Structure (5 sections, 16 equations, 3 figures, 1 algorithm)

This paper contains 5 sections, 16 equations, 3 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System and Channel Models
  3. Problem Formulation
  4. Simulation Results and Discussion
  5. Conclusion

Figures (3)

  • Figure 1: The considered FIRES-aided communication system.
  • Figure 2: Illustration of examples of the optimized positions when the FIRES has (a) $M=4$; (b) $M=9$; and (c) $M=16$ fluid elements.
  • Figure 3: Effective rate versus: (a) number of iterations of Algorithm \ref{['algo1']} for different numbers $M$ of FIRES fluid elements when $P=40$ dBm; (b) transmit power $P$ for different $M$; and (c) size of FIRES $A$ for different $M$ when $P=40$ dBm and $N_h^m=N_v^m=100$.