论文标题
可重新配置的智能表面辅助无线感应场景深度估计
Reconfigurable Intelligent Surface Aided Wireless Sensing for Scene Depth Estimation
论文作者
论文摘要
当前的场景深度估计方法主要依赖于光学传感，这带来了隐私问题，并且对遥远，闪亮和透明的表面/对象的估计含糊不清。可重新配置的智能表面（RISS）为使用低成本和节能的体系结构提供了大量天线的途径。这有可能通过高空间分辨率实现RIS辅助无线传感。在本文中，我们建议采用RIS辅助无线传感系统进行场景深度估算。我们开发了一个综合框架，使用RIS AID的MMWave传感系统来构建准确的深度图。在此框架中，我们提出了一个新的RIS交互代码手册，能够创建反射光束的传感网格，以符合有效的场景深度映射构造的理想特征。使用设计的代码簿，对接收的信号进行处理以构建高分辨率深度图。仿真结果将提出的解决方案与基于RGB的方法进行了比较，并强调了在场景深度感知中采用RIS AID MMWAVE感应的希望。
Current scene depth estimation approaches mainly rely on optical sensing, which carries privacy concerns and suffers from estimation ambiguity for distant, shiny, and transparent surfaces/objects. Reconfigurable intelligent surfaces (RISs) provide a path for employing a massive number of antennas using low-cost and energy-efficient architectures. This has the potential for realizing RIS-aided wireless sensing with high spatial resolution. In this paper, we propose to employ RIS-aided wireless sensing systems for scene depth estimation. We develop a comprehensive framework for building accurate depth maps using RIS-aided mmWave sensing systems. In this framework, we propose a new RIS interaction codebook capable of creating a sensing grid of reflected beams that meets the desirable characteristics of efficient scene depth map construction. Using the designed codebook, the received signals are processed to build high-resolution depth maps. Simulation results compare the proposed solution against RGB-based approaches and highlight the promise of adopting RIS-aided mmWave sensing in scene depth perception.
