# RIS-Based On-the-Air Semantic Communications -- a Diffractional Deep Neural Network Approach

arXiv: https://arxiv.org/abs/2312.00535 · HTML: https://mlsanity.com/paper/2312.00535/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 17 references that are in the map.
- First posted on arXiv 1 Dec 2023.

## Builds on (most cited first, 8 of 8)

- [Deep Complex Networks](https://mlsanity.com/paper/1705.09792/) (2017)
- [Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems](https://mlsanity.com/paper/2104.13386/) (2021)
- [Semantic Communication Systems for Speech Transmission](https://mlsanity.com/paper/2102.12605/) (2021)
- [Wireless Deep Video Semantic Transmission](https://mlsanity.com/paper/2205.13129/) (2022)
- [Metasurface-Enabled On-Chip Multiplexed Diffractive Neural Networks in the Visible](https://mlsanity.com/paper/2107.07873/) (2021)
- [AirNN: Neural Networks with Over-the-Air Convolution via Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/2202.03399/) (2022)
- [MIMO Transmission through Reconfigurable Intelligent Surface: System Design, Analysis, and Implementation](https://mlsanity.com/paper/1912.09955/) (2019)
- [Stacked Intelligent Metasurfaces for Multiuser Downlink Beamforming in the Wave Domain](https://mlsanity.com/paper/2309.02687/) (2023)

## Built on by (most cited first, 1 of 1)

- [Over-the-Air Edge Inference via End-to-End Metasurfaces-Integrated Artificial Neural Networks](https://mlsanity.com/paper/2504.00233/) (2025)

## Abstract (arXiv)

Semantic communication has gained significant attention recently due to its advantages in achieving higher transmission efficiency by focusing on semantic information instead of bit-level information. However, current AI-based semantic communication methods require digital hardware for implementation. With the rapid advancement on reconfigurable intelligence surfaces (RISs), a new approach called on-the-air diffractional deep neural networks (D2NN) can be utilized to enable semantic communications on the wave domain. This paper proposes a new paradigm of RIS-based on-the-air semantic communications, where the computational process occurs inherently as wireless signals pass through RISs. We present the system model and discuss the data and control flows of this scheme, followed by a performance analysis using image transmission as an example. In comparison to traditional hardware-based approaches, RIS-based semantic communications offer appealing features, such as light-speed computation, low computational power requirements, and the ability to handle multiple tasks simultaneously.