Eleni Theodoropoulou

The 6G-EWOC project seeks to create an AI-enhanced fiber-wireless optical 6G network to support advanced use cases for Fully Autonomous Vehicles (FAVs) by establishing a new access network incorporating the integration of both fixed/wireless optical and wireless/RF technologies. The access network will be supported by a fast, reconfigurable, highly dynamic and customizable optical fiber-based fronthaul infrastructure which will minimize optoelectronic transitions through tunable and programmable devices, as well as low energy photonic switching of (packet/optical) spectrum and spatial resources, managed by AI-enabled SDN. End-to-end connectivity between AI-based edge computation units will enable advanced Connected and Automated Mobility (CAM) services over a rapid, adaptable network architecture.

In future mobile networks, the evolution of optical transport architectures enabling the flexible, scalable interconnection of Baseband Units (BBUs) and Radio Units (RUs) with heterogeneous interfaces is a significant issue. In this paper, we propose a multi-technology hybrid transport architecture that comprises both analog and digital-Radio over Fiber (RoF) mobile network segments relying on a dynamically reconfigurable optical switching node. As a step forward, the integration of the discussed network layout into an existing mobile infrastructure is demonstrated, enabling the support of real-world services through both standard digital and Analog–Intermediate- Frequency over Fiber (A-IFoF)-based converged fiber–wireless paths. Emphasis has been placed on the implementation of a real-time A-IFoF transceiver that is employed through a single embedded fully programmable gateway array (FPGA)-based platform that serves as an Ethernet to Intermediate Frequency (IF) bridge for the transmission of legacy traffic over the analog network segment. The experimental evaluation of the proposed concept was based on the dynamic optical routing of the legacy Common Public Radio Interface (CPRI), 1.5 GBaud analog-intermediate frequency-over-fiber (A-IFoF)/mmWave and 10 Gbps binary optical waveforms, showing acceptable error vector magnitude (EVM) values for the complex radio waveforms and error-free operation for binary optical streams, with Bit Error Rate (BER) values less than 10⁻⁹. Finally, the end-to-end proof-of-concept demonstration of the proposed solution was achieved through the delivery of 4K video streaming and Internet Protocol (IP) calls over a mobile core network.

5G networks are shaping a new ecosystem necessitating various transformations of the existing network infrastructures combined with the use of network softwarization and programmability, so as to satisfy the needs of all the involved stakeholders (telecom/service providers, infrastructure owners, tenants, vertical industries, end-users, etc.), while a wide range of issues have to be addressed spanning from technology to business domains. The 5G-PPP project 5G-PHOS [ 1 ] proposes a novel framework to allow telecom operators and service providers to overcome 5G densification issues while supporting the stringent 5G requirements in a flexible and cost efficient manner to allow for commercialization. This paper aims at providing indicative architectural instantiations of the 5G-PHOS solution, depicting the way the technology supports the 5G requirements and the stakeholders’ needs along with the functionalities and the deployment feasibility of an ambitious 5G fronthaul/backhaul network solution.

This article presents a converged 5G network infrastructure and an overarching architecture to jointly support operational network and end-user services, proposed by the EU 5G PPP project 5G-XHaul. The 5G-XHaul infrastructure adopts a common fronthaul/backhaul network solution, deploying a wealth of wireless technologies and a hybrid active/passive optical transport, supporting flexible fronthaul split options. This infrastructure is evaluated through a novel modeling. Numerical results indicate significant energy savings at the expense of increased end-user service delay.