Emulation of Point Cloud Streaming over 5G Network
Estabraq H. Makiyah, Nassr N. Khamees · Research Square · 2023
Abstract Realistic digital representations of 3D objects and environments are now achievable because to recent developments in computer graphics, enabling real-time user interactions. Creating effective compression techniques and technologies that may take into account varied application limits has become a crucial problem due to the rising need for various point clouds. Future wireless networks are expected to undergo a paradigm change as a result of the 3GPP's 5G Advanced development. In this paper, we propose a complete system for streaming 3D high density point cloud data using a web-based streaming server with HTTP/2 protocol enabled, and compare results in two scenarios over WIFI and over 5G standalone network. Results have shown great outperformance over conventional work by decreasing inter-frame latency for large point cloud streaming by 16.8% for the case of 4 million points using http/2 over wifi, and by 71.51% over emulated 5G network. Streamed packets were also captured showing an increased frame rate of the same sample by 20.7% and 353% for the cases of wifi and 5G networks, respectively.