Year: 2024
Type: article
Abstract: Ultra-massive interconnection composed of extremely small to minuscule networks that are significantly overloaded is required for the fifth generation (5G) and the next sixth generation (6G) networks. In order to meet the demands for network flexibility, complete coverage, and huge access, the conventional radio access network (RAN) will be completely revamped. This study focuses on the technological trends in the requirements-fulfilling Open RAN (ORAN) architecture and essential technologies in this regard. In particular, the study investigates the potential of Radio over Fibre (RoF) and Passive Optical Networks (PON) for Open Optical Front Hauls (OOFH) and trends in AI algorithms, for enhancing system performance and network intelligence simultaneously. The article showcases experimental results using OpenRAN Gym, an open-source, practical platform designed for end-to-end system design, data collection, and testing workflows aimed at intelligent control in next-generation Open RAN systems. Two xApps developed with OpenRAN Gym are demonstrated, managing a large-scale network of 10 base stations and 60 users deployed on the Colosseum testbed. Performance is assessed by analyzing transmitted packets and buffer occupancy. Additionally, an OFH system with Analog RoF is tested, using linearisation techniques to reduce the Error Vector Magnitude (EVM) to below 2%. The study also includes an experimental MIMO Fi-Wi OFH case, where a 5G new radio waveform achieves a 3% EVM, complying with the 3GPP standards.
Authors: Hamna Shoukat, Nelofar Aslam, Muhammad Waseem, Muhammad Usman Hadi
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4404899444