# Cloud-RAN functional split for an efficient fronthaul network

arXiv: https://arxiv.org/abs/2101.04216 · HTML: https://mlsanity.com/paper/2101.04216/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jan 2021.

## Built on by (most cited first, 4 of 4)

- [A Survey on XAI for 5G and Beyond Security: Technical Aspects, Challenges and Research Directions](https://mlsanity.com/paper/2204.12822/) (2022)
- [Learning-Based Latency-Constrained Fronthaul Compression Optimization in C-RAN](https://mlsanity.com/paper/2311.03899/) (2023)
- [ML-based handover prediction over a real O-RAN deployment using RAN Intelligent controller](https://mlsanity.com/paper/2404.19671/) (2024)
- [Scalable Multivariate Fronthaul Quantization for Cell-Free Massive MIMO](https://mlsanity.com/paper/2409.06715/) (2024)

## Abstract (arXiv)

The evolution of telecommunication network towards cloud-native environments enables flexible centralization of the base band processing of radio signals. There is however a trade-off between the centralization benefits and the fronthaul cost for carrying the radio data between distributed antennas and data processing centers, which host the virtual RAN functions. In this paper, we present a specific split solution for an efficient fronthaul, which enables reducing the consumed bandwidth while being compliant with advanced cooperative radio technologies (interference reduction and data rate improvements). The proposed split has been implemented on the basis of Open Air Interface code and shows important gains in the required fronthaul bandwidth as well as significant latency reduction in the processing of radio frames.  Publisher: IEEE  ISBN:978-1-7281-3130-6