Point Cloud in the Air
Yulin Shao Chenghong Bian Li Yang Qianqian Yang Zhaoyang Zhang Deniz Gunduz
Acquisition and processing of point clouds (PCs) is a crucial enabler for
many emerging applications reliant on 3D spatial data, such as robot
navigation, autonomous vehicles, and augmented reality. In most scenarios, PCs
acquired by remote sensors must be transmitted to an edge server for fusion,
segmentation, or inference. Wireless transmission of PCs not only puts on
increased burden on the already congested wireless spectrum, but also confronts
a unique set of challenges arising from the irregular and unstructured nature
of PCs. In this paper, we meticulously delineate these challenges and offer a
comprehensive examination of existing solutions while candidly acknowledging
their inherent limitations. In response to these intricacies, we proffer four
pragmatic solution frameworks, spanning advanced techniques, hybrid schemes,
and distributed data aggregation approaches. In doing so, our goal is to chart
a path toward efficient, reliable, and low-latency wireless PC transmission.