# Anti-Jamming Sensing with Distributed Reconfigurable Intelligent Metasurface Antennas

arXiv: https://arxiv.org/abs/2508.04964 · HTML: https://mlsanity.com/paper/2508.04964/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 39 references that are in the map.
- First posted on arXiv 7 Aug 2025.

## Builds on (most cited first, 12 of 12)

- [Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming](https://mlsanity.com/paper/1810.03961/) (2018)
- [EfficientFi: Towards Large-Scale Lightweight WiFi Sensing via CSI Compression](https://mlsanity.com/paper/2204.04138/) (2022)
- [Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-user Communications: Achievable Rates with Limited Discrete Phase Shifts](https://mlsanity.com/paper/1910.14328/) (2019)
- [AutoFi: Towards Automatic WiFi Human Sensing via Geometric Self-Supervised Learning](https://mlsanity.com/paper/2205.01629/) (2022)
- [Target Sensing with Intelligent Reflecting Surface: Architecture and Performance](https://mlsanity.com/paper/2201.09091/) (2022)
- [MetaSensing: Intelligent Metasurface Assisted RF 3D Sensing by Deep Reinforcement Learning](https://mlsanity.com/paper/2011.12515/) (2020)
- [RISAR: RIS-assisted Human Activity Recognition with Commercial Wi-Fi Devices](https://mlsanity.com/paper/2402.17277/) (2024)
- [Holographic Integrated Sensing and Communications: Principles, Technology, and Implementation](https://mlsanity.com/paper/2211.08646/) (2022)
- [Intelligent Surface Empowered Sensing and Communication: A Novel Mutual Assistance Design](https://mlsanity.com/paper/2212.12909/) (2022)
- [Integrated Sensing and Communication Under DISCO Physical-Layer Jamming Attacks](https://mlsanity.com/paper/2404.07477/) (2024)
- [Multi-user Downlink with Reconfigurable Intelligent Metasurface Antennas (RIMSA) Array](https://mlsanity.com/paper/2506.18418/) (2025)
- [Dynamic Agile Reconfigurable Intelligent Surface Antenna (DARISA) MIMO: DoF Analysis and Effective DoF Optimization](https://mlsanity.com/paper/2507.19136/) (2025)

## Abstract (arXiv)

The utilization of radio frequency (RF) signals for wireless sensing has garnered increasing attention. However, the radio environment is unpredictable and often unfavorable, the sensing accuracy of traditional RF sensing methods is often affected by adverse propagation channels from the transmitter to the receiver, such as fading and noise. In this paper, we propose employing distributed Reconfigurable Intelligent Metasurface Antennas (RIMSA) to detect the presence and location of objects where multiple RIMSA receivers (RIMSA Rxs) are deployed on different places. By programming their beamforming patterns, RIMSA Rxs can enhance the quality of received signals. The RF sensing problem is modeled as a joint optimization problem of beamforming pattern and mapping of received signals to sensing outcomes. To address this challenge, we introduce a deep reinforcement learning (DRL) algorithm aimed at calculating the optimal beamforming patterns and a neural network aimed at converting received signals into sensing outcomes. In addition, the malicious attacker may potentially launch jamming attack to disrupt sensing process. To enable effective sensing in interferenceprone environment, we devise a combined loss function that takes into account the Signal to Interference plus Noise Ratio (SINR) of the received signals. The simulation results show that the proposed distributed RIMSA system can achieve more efficient sensing performance and better overcome environmental influences than centralized implementation. Furthermore, the introduced method ensures high-accuracy sensing performance even under jamming attack.