Low Latency Scalable Point Cloud Communication

Mobile edge and V2V Low latency streaming of 3D information is a crucial technology for smart city and autonomous driving. In this paper, we propose a joint source-channel coding framework for transmitting 3D point cloud data to different quality-of-service devices by creating a scalable representation of point cloud. We employ a scalable Binary Tree embedded Quad Tree point cloud encoder with adaptive modulation and coding schemes to guarantee the latency as well as the quality requirement of each user. We perform link level simulations using outdoor 3D point cloud dataset from LiDAR scans for auto-driving. The scalability of our encoded point cloud provides a trade-off in the received voxel size/quality vs channel condition under a hard latency constraint. The users with good channel conditions receive a near lossless point cloud whereas users with bad channel conditions are still able to receive at least the base layer point cloud.