Toward 6G Optical Fronthaul: A Survey on Enabling Technologies and Research Perspectives
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Abstract (arXiv)
The anticipated launch of the Sixth Generation (6G) of mobile technology by 2030 will mark a significant milestone in the evolution of wireless communication, ushering in a new era with advancements in technology and applications. 6G is expected to deliver ultra-high data rates and almost instantaneous communications, with three-dimensional coverage for everything, everywhere, and at any time. In the 6G Radio Access Networks (RANs) architecture, the Fronthaul connects geographically distributed Remote Units (RUs) to Distributed/Digital Units (DUs)pool. Among all possible solutions for implementing 6G fronthaul, optical technologies will remain crucial in supporting the 6G fronthaul, as they offer high-speed, low-latency, and reliable transmission capabilities to meet the 6G strict requirements. This survey provides an explanation of the 5G and future 6G optical fronthaul concept and presents a comprehensive overview of the current state of the art and future research directions in 6G optical fronthaul, highlighting the key technologies and research perspectives fundamental in designing fronthaul networks for 5G and future 6G. Additionally, it examines the benefits and drawbacks of each optical technology and its potential applications in 6G fronthaul networks. This paper aims to serve as a comprehensive resource for researchers and industry professionals about the current state and future prospects of 6G optical fronthaul technologies, facilitating the development of robust and efficient wireless networks of the future.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Jun 2024.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025Generalized few-shot transfer learning architecture for modeling the EDFA gain spectrumcited by 0
- 2026SEAL: An Open, Auditable, and Fair Data Generation Framework for AI-Native 6G Networkscited by 0
- 2026Link-adaptive digital twin for robust physical-layer modeling in hybrid-amplified ultra-wideband optical networkscited by 0
- 2026Link-adaptive digital twin for robust physical-layer modeling in hybrid-amplified ultra-wideband optical networks11 Aug 2026
- 2026SEAL: An Open, Auditable, and Fair Data Generation Framework for AI-Native 6G Networks2 Apr 2026
- 2025Generalized few-shot transfer learning architecture for modeling the EDFA gain spectrum29 Jul 2025