Abstract

Integration of public fifth generation mobile network (5G) backhaul and non-public networks is key for the private/local 5G network ecosystem. However, such shared networks, namely, x-haul, must satisfy the extremely diverse traffic demands including low latency and massive number of internet of things (IoT) devices. We propose an x-haul platform with autonomous time aware shaper and adaptive mobile fronthaul compression, which simultaneously accommodates two 5G NR-class fronthauls (2*29.5 Gbps CPRI-equivalent rate) and backhaul traffic with 1,000 IoT devices. From an experiment we conducted to evaluate the proposed platform, mobile fronthaul traffic was transferred with 76-μs deterministic latency via 4 switches and 10-km optical fiber by autonomous time aware shaper while improving the achievable transmission rate of IoT traffic owing to the integration of adaptive compression.

Autonomous dynamic window shaping and rerouting for a service-converged layer-2 network with a time-aware shaper accommodating mobile fronthaul and IoT backhaul

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J. Opt. Commun. Netw. 13(5) 108-115 (2021)

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100 Gbps quantum-secured and O-RAN-enabled programmable optical transport network for 5G fronthaul

Ekin Arabul, Romerson D. Oliveira, Amin Emami, Stavros Typos, Constantinos Vrontos, Rui Wang, Reza Nejabati, and Dimitra Simeonidou
J. Opt. Commun. Netw. 15(8) C223-C231 (2023)

AI-assisted intent-based traffic grooming in a dynamically shared 5g optical fronthaul network

Luyao Guan, Min Zhang, Yihan Gui, Chunyu Zhang, Hui Yang, Anthony C. Boucouvalas, and Danshi Wang
Opt. Express 29(15) 23113-23130 (2021)

Hierarchical Edge Cloud Enabling Network Slicing for 5G Optical Fronthaul

Chuang Song, Min Zhang, Yueying Zhan, Danshi Wang, Luyao Guan, Wei Liu, Lin Zhang, and Siya Xu
J. Opt. Commun. Netw. 11(4) B60-B70 (2019)