In this paper, we address the virtualization and the centralization of real-time network functions, notably in the framework of Cloud RAN (C-RAN). We thoroughly analyze the required fronthaul capacity for the deployment of the proposed C-RAN architecture. We are specifically interested in the performance of the software based channel coding function. We develop a dynamic multi-threading approach to achieve parallel computing on a multi-core platform. Measurements from an OAI-based testbed show important gains in terms of latency; this enables the increase of the distance between the radio elements and the virtualized RAN functions and thus a higher aggregation of gNodeBs in edge data centers, referred to as Central Offices (COs).
@article{arxiv.1905.01141,
title = {Higher aggregation of gNodeBs in Cloud-RAN architectures via parallel computing},
author = {Veronica Quintuna Rodriguez and Fabrice Guillemin},
journal= {arXiv preprint arXiv:1905.01141},
year = {2019}
}