Skip to main content

Analog vs. Next-Generation Digital Fronthaul: How to Minimize Optical Bandwidth Utilization

Hinrichs, Malte and Fernández del Rosal, Luz and Kottke, Christoph and Jungnickel, Volker (2017) Analog vs. Next-Generation Digital Fronthaul: How to Minimize Optical Bandwidth Utilization. In: 2017 International Conference on Optical Network Design and Modeling (ONDM). IEEE. ISBN 978-1-5090-4006-3. E-ISBN 978-3-901882-93-7. (doi:10.23919/ONDM.2017.7958539) (KAR id:64095)

PDF Author's Accepted Manuscript
Language: English
Download (603kB) Preview
[thumbnail of 18_Hinrichs_NextGenerationFronthaul.pdf]
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL


In this paper we investigate two promising approaches to reduce the optical bandwidth utilization in the mobile fronthaul of next-generation cloud radio access networks. We analyze and compare the performance of an analog radioover-fiber and a new digital fronthaul in a chromatic dispersionlimited scenario. The former uses several analog channels, generated by up- and down-converting of baseband signals, and the latter utilizes simple OOK NRZ for the transmission to the remote radio head. Both principles are applied to a custom millimeter-wave system, consisting of several analog channels with baseband bandwidths as expected for 5G. The performance of both concepts at transmission rates of up to 100 Gb/s and 100 km of fiber is evaluated. We will show that both approaches are suitable for transmission distances typical for fronthaul and discuss their advantages and disadvantages. Furthermore, an optimized bandwidth concept for the analog radio-over-fiber system is presented, which enables transmission distances on the scale of metro networks.

Item Type: Book section
DOI/Identification number: 10.23919/ONDM.2017.7958539
Uncontrolled keywords: analog fronthaul, next-generation digital fronthaul, intermediate frequencies-over-fiber (IFoF), next-generation mobile network (5G), millimeter wave (mm-wave)
Subjects: Q Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Kornelia Jumel
Date Deposited: 20 Oct 2017 09:52 UTC
Last Modified: 16 Feb 2021 13:49 UTC
Resource URI: (The current URI for this page, for reference purposes)
  • Depositors only (login required):


Downloads per month over past year