BEAM
Vol. 2 No. 1 November (2026): Bridging of Emerging AI and Media Broadcasting

Semantic Edge Orchestration for 6G-Enabled Immersive Media Broadcasting

Lunantari Sanbella (Rey Incorporation)
Chandra Lukita (Catur Insan Cendekia University)
Anandha Fitriani (CAI Sejahtera Indonesia)
Ihda Nur Fathiyah (Syarif Hidayatullah Jakarta Islamic State University)



Article Info

Publish Date
11 Sep 2026

Abstract

The rapid evolution of 6G networks is expected to transform immersive media broadcasting by enabling ultra-low-latency communication, intelligent edge computing, and high-capacity transmission for extended reality, holographic content, and interactive multimedia. However, conventional edge resource management remains limited in understanding the semantic importance of media content, resulting in inefficient computation and transmission when network resources fluctuate. This study aims to develop a Semantic Edge Orchestration framework for 6G-enabled immersive media broadcasting that dynamically prioritizes computational, communication, and caching resources according to the semantic relevance of media streams and real-time network conditions. The proposed framework integrates semantic feature extraction, edge intelligence, and adaptive resource orchestration to classify content importance and coordinate processing across distributed edge nodes. Its performance is evaluated through simulation under different traffic loads and network conditions using end-to-end latency, bandwidth utilization, edge resource efficiency, and immersive media quality as evaluation metrics. The experimental results demonstrate that the proposed approach reduces end-to-end latency by 27.8%, decreases bandwidth consumption by 22.4%, and improves edge resource utilization by 18.6% compared with conventional resource aware orchestration while maintaining consistent perceptual quality during high network loads. These findings indicate that semantic aware edge orchestration can provide an effective architecture for intelligent 6G broadcasting by allocating network resources according to both contextual content importance and infrastructure conditions, thereby supporting scalable, responsive, and resource-efficient delivery of next- generation immersive media services.

Copyrights © 2026






Journal Info

Abbrev

beam

Publisher

Subject

Description

Bridging of Emerging AI and Media Broadcasting (BEAM) is an international, peer-reviewed, open-access journal dedicated to the intersection of artificial intelligence, telecommunications engineering, and digital media studies. The journal provides a high-impact platform for researchers, engineers, ...