# Wireless Communications with Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement

arXiv: https://arxiv.org/abs/1911.05326 · HTML: https://mlsanity.com/paper/1911.05326/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2019.

## Built on by (most cited first, 9 of 9)

- [Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/2205.03793/) (2022)
- [CSIT-Free Model Aggregation for Federated Edge Learning via Reconfigurable Intelligent Surface](https://mlsanity.com/paper/2102.10749/) (2021)
- [Graph Attention Networks for Channel Estimation in RIS-assisted Satellite IoT Communications](https://mlsanity.com/paper/2104.00735/) (2021)
- [Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA](https://mlsanity.com/paper/2104.01414/) (2021)
- [Personalized Over-the-Air Federated Learning with Personalized Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/2401.12149/) (2024)
- [Neural Channel Knowledge Map Assisted Scheduling Optimization of Active IRSs in Multi-User Systems](https://mlsanity.com/paper/2508.07009/) (2025)
- [RadioFormer3D: Weakly Supervised 3D Radio Map Estimation in Low-Altitude Airspace via Generative Modeling](https://mlsanity.com/paper/2605.29538/) (2026)
- [Hybrid-Field Sparse Channel Representation and Recovery for XL-RIS-Assisted mmWave MIMO Systems](https://mlsanity.com/paper/2608.00052/) (2026)
- [RAOA: Alternating-Operator Neural Computation with Programmable Radio Propagation](https://mlsanity.com/paper/2610.02683/) (2026)

## Abstract (arXiv)

Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cells have recently drawn significant attention due to their superior capability in manipulating electromagnetic waves. In particular, RIS-assisted wireless communications have the great potential to achieve significant performance improvement and coverage enhancement in a cost-effective and energy-efficient manner, by properly programming the reflection coefficients of the unit cells of RISs. In this paper, free-space path loss models for RIS-assisted wireless communications are developed for different scenarios by studying the physics and electromagnetic nature of RISs. The proposed models, which are first validated through extensive simulation results, reveal the relationships between the free-space path loss of RIS-assisted wireless communications and the distances from the transmitter/receiver to the RIS, the size of the RIS, the near-field/far-field effects of the RIS, and the radiation patterns of antennas and unit cells. In addition, three fabricated RISs (metasurfaces) are utilized to further corroborate the theoretical findings through experimental measurements conducted in a microwave anechoic chamber. The measurement results match well with the modeling results, thus validating the proposed free-space path loss models for RIS, which may pave the way for further theoretical studies and practical applications in this field.