Distributed RIS-Based Sensing of Mobile Passive Obstacles in Dense mmWave Networks

The millimeter-wave (mmWave) technology offers unprecedented potential to meet the growing demand for highspeed data communications. However, it is also highly sensitive to radio obstructions, which can significantly degrade the quality of service and require frequent handover operations. Anticipating such blockages through environment sensing is therefore critical for efficient radio resource management and improved network performance. In this context, this paper proposes an opportunistic and cooperative sensing approach based on spatially distributed dual-beam reflective Reconfigurable Intelligent Surfaces (RISs). These surfaces scan the environment and reflect toward sensing nodes the ambient signal power from a plurality of noncoherent sources. By analyzing the power fluctuations eventually caused by transient shadowing, the presence of a mobile blocker is first detected in angular sectors centered around the RISs. This information can then be shared and fused to position the blocker in 2D. As passive surfaces can suffer from significant power losses and irregular beam patterns leading respectively to false alarms and missed detections, we thus consider selecting and/or weighting the RIS-wise detection observations that feed the final cooperative positioning stage, relying on empirical reliability indicators inspired by image processing. Simulation results in a dense mmWave scenario illustrate benefits from selective multi-RIS cooperation.