Integração de uma aplicação de realidade aumentada com sistemas 5G seguindo o padrão 3GPP

Abstract

Based on the standards defined by the 3rd Generation Partnership Project (3GPP), this work validates the 5G Media Streaming (5GMS) model, using the MR-Leo prototype as a case study. MR-Leo is a Mixed Reality (MR) application designed to explore the potential of these technologies in high-demand computational environments. The study begins with a review of advancements enabled by 5G networks, emphasizing their ability to provide low-latency connectivity, high bandwidth, and support for heterogeneous devices at scale. Additionally, the frameworks CAPIF and SEAL are discussed as tools to facilitate interoperability and API management in the 5G architecture, though recognized for their technical complexity and limited practical adoption. Edge computing is then investigated as a strategic component capable of bringing computational resources closer to end users, reducing latencies and enhancing the performance of intensive algorithms critical for MR applications. The validation of the proposed study was carried out in three distinct scenarios: a local controlled environment, an emulated 5G network, and a real 5G callbox. Experimental evaluation demonstrated the superiority of the protocol combined with video compression, achieving consistent metrics that meet the key performance indicators (KPIs) defined in the literature. The comparative qualitative analysis highlighted significant compatibilities as well as gaps, such as the absence of a functional component equivalent to the 5GMS Application Function (AF). In this regard, this work makes important contributions by demonstrating the technical feasibility of delivering MR services on 5G networks through edge computing.