ENabling Intelligent Omni-surfaces for Smart and efficient wireless communication

Project Information

ENIOS

Grant agreement ID: 101107993

DOI

10.3030/101107993

Project closed

EC signature date 7 July 2023

Start date 1 September 2024

End date 31 August 2026

Funded under

• Marie Skłodowska-Curie Actions (MSCA)

Total cost

No data

EU contribution

€ 165 312,96

Coordinated by

UNIVERSIDAD DE GRANADA
Spain

Periodic Reporting for period 1 - ENIOS (ENabling Intelligent Omni-surfaces for Smart and efficient wireless communication)

Reporting period: 2024-09-01 to 2026-08-31

Summary of the context and overall objectives of the project

Wireless connectivity has become essential for communication, education, transport, healthcare, industry and many other services. Future sixth-generation (6G) networks are expected to accommodate rapidly increasing data traffic, connected devices and intelligent applications while providing high reliability, broad coverage, low latency and improved energy and spectrum efficiency. However, conventional wireless systems mainly adapt the transmitter and receiver, while the propagation environment itself remains largely uncontrolled.

Reconfigurable intelligent surfaces offer a promising way to make the wireless environment programmable. Most conventional surfaces can only reflect signals and therefore mainly serve users located on one side of the surface. Simultaneously transmitting and reflecting intelligent omni-surfaces can serve users on both sides, potentially providing more flexible and nearly full-space wireless coverage. Nevertheless, many existing studies rely on idealised models that do not sufficiently account for physical constraints, spatial correlation, propagation effects, imperfect surface control and the dependence between transmission and reflection characteristics. This can lead to unrealistic performance predictions and limit the practical design of these technologies.

ENIOS aimed to establish realistic foundations for intelligent omni-surface-assisted communication beyond 5G and towards 6G. Its first objective was to develop physically motivated mathematical and statistical channel models that capture relevant propagation conditions, implementation constraints and dependence structures. Its second objective was to create analytical tools for evaluating system performance, including reliability, achievable rate, coverage, multiple access and secure communication. Its third objective was to investigate new adaptive architectures combining intelligent surfaces with spatially reconfigurable and fluid antenna concepts.

The project’s pathway to impact is based on translating physical characteristics into tractable models, using these models to derive and validate communication performance results, and making the resulting knowledge available to the research community. In the short term, these outcomes provide researchers and engineers with more reliable tools for comparing and designing emerging 6G technologies. In the longer term, they can support further simulation, experimental validation, standardisation and technology development. ENIOS therefore contributes to the European ambition of developing secure, sustainable and energy efficient digital connectivity and may ultimately support more reliable wireless services for citizens, industry and connected infrastructure.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The scientific work was organised around the development of realistic channel models, analytical performance tools and new adaptive surface and antenna architectures for future wireless networks.

First, physically motivated models were developed for communication systems assisted by simultaneously transmitting and reflecting intelligent surfaces, reconfigurable intelligent surfaces and fluid antenna systems. The work examined practical effects that are often simplified in conventional models, including spatial correlation, dependence between channel components, phase mismatch, imperfect surface control and complex propagation conditions. Multivariate statistical and copula-based methods were investigated to represent dependence structures that cannot always be described accurately using conventional linear correlation models.

Second, the resulting channel models were incorporated into analytical frameworks for evaluating communication performance. Mathematical expressions and computational methods were developed to study outage probability, coverage, achievable performance, reliability, multiple access, backscatter communication, covert communication and physical layer security. The analysis considered different system architectures, including rate-splitting and non-orthogonal multiple access schemes, unmanned aerial vehicle-assisted links and reconfigurable surface-assisted backscatter networks. The theoretical findings were verified through extensive numerical and Monte Carlo simulations.

Third, ENIOS investigated architectures that combine intelligent surfaces with spatially reconfigurable and fluid antenna technologies. This work included fluid reconfigurable intelligent surfaces, in which the effective positions of radiating or reflecting elements can be adapted within a surface. A main achievement was the introduction of the Fluid Integrated Reflecting and Emitting Surface (FIRES) concept. This architecture combines simultaneous transmission and reflection with spatial reconfigurability, enabling the surface elements to adjust their positions and control coefficients to serve users located on both sides of the surface.

Overall, the project produced a unified body of models and performance results for adaptive wireless environments. The results identified when spatial reconfiguration can improve coverage, reliability and secure communication, while also revealing the effects of correlation, hardware imperfections and system-design constraints. These outcomes provide a technical foundation for the continued investigation and future experimental validation of intelligent surface and fluid antenna technologies for 6G networks.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

ENIOS advanced the state of the art by moving beyond idealised models of intelligent surfaces and adaptive antennas. Many earlier studies assumed independent control coefficients, simplified propagation conditions or fixed element positions. The project instead developed dependence-aware and physically motivated modelling approaches that account for spatial correlation, phase mismatch, implementation imperfections and the interaction between different components of the wireless channel. This provides a more realistic basis for predicting the performance of emerging reconfigurable wireless technologies.

The project also extended analytical performance evaluation to several emerging applications. The developed frameworks characterised reliability, coverage, multiple access, backscatter communication, covert communication and physical-layer security in systems assisted by intelligent surfaces and fluid antennas. The results provided tractable analytical expressions and simulation-based validation, allowing important design trade-offs to be identified without relying exclusively on computationally intensive system-level simulations.

A key result beyond the state of the art was the introduction of the Fluid Integrated Reflecting and Emitting Surface concept. Unlike a conventional fixed intelligent surface, this architecture combines simultaneous transmission and reflection with spatially reconfigurable surface elements. It therefore introduces additional control over element position, transmission and reflection characteristics, creating new possibilities for adaptable full-space wireless coverage. The project also developed results for fluid reconfigurable intelligent surfaces and for the integration of fluid antennas with multiple-access, aerial, backscatter and secure communication systems.

These results can support more accurate comparison, optimisation and design of candidate technologies for future 6G networks. Their potential impact includes improved coverage, reliability, spectrum use, energy efficiency and communication security. However, the results remain at an early, pre-competitive stage. Further uptake will require electromagnetic and hardware prototyping, measurement-based channel validation, scalable channel estimation and control algorithms, real-time implementation studies and closer collaboration with industrial and standardisation communities. Open and reproducible research outputs will also be important for independent validation and continued development.