用事件相机实现不直视的光无线通信，靠物体反射解码数据。
Non Line-of-Sight Optical Wireless Communication using Neuromorphic Cameras
- 用事件相机捕捉光照变化，异步解码反射光信号。
- 自适应多脉冲调制提升速率与抗干扰能力，实测有效。
- 光滑浅色物体更适合，大件或哑光物易受多路径干扰。
受生物视觉启发的事件相机以高时间分辨率和高效性捕捉光照变化，输出事件流而非传统图像。本文探索其在被动式光无线通信（OWC）中的应用，利用其对光照变化的异步检测能力，通过日常物体反射解码传输数据。提出一种基于事件相机的被动可见光通信（VLC）系统，将该技术扩展至非直视（NLoS）场景。实验验证了可行性，对比了传统开关键控（OOK）与先进N脉冲调制方案。引入自适应N脉冲调制，根据数据包比特组成动态调整编码，显著提升不同场景下的数据速率与鲁棒性。结果表明，浅色光滑物体更利于NLoS通信，而大尺寸或哑光物体因多路径反射导致误码率升高。
原文摘要 · Abstract (English)
Neuromorphic or event cameras, inspired by biological vision systems, capture changes in illumination with high temporal resolution and efficiency, producing streams of events rather than traditional images. In this paper, we explore the use of neuromorphic cameras for passive optical wireless communication (OWC), leveraging their asynchronous detection of illumination changes to decode data transmitted through reflections of light from objects. We propose a novel system that utilizes neuromorphic cameras for passive visible light communication (VLC), extending the concept to Non Line-of-Sight (NLoS) scenarios through passive reflections from everyday objects. Our experiments demonstrate the feasibility and advantages of using neuromorphic cameras for VLC, characterizing the performance of various modulation schemes, including traditional On-Off Keying (OOK) and advanced N-pulse modulation. We introduce an adaptive N-pulse modulation scheme that dynamically adjusts encoding based on the packet's bit composition, achieving higher data rates and robustness in different scenarios. Our results show that lighter-colored, glossy objects are better for NLoS communication, while larger objects and those with matte finishes experience higher error rates due to multipath reflections.
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