November 22, 2021
The increasing digitization of society and industry will soon push the current network infrastructure to the limits of its capacity. In the collaborative STARFALL project (Scalable Terminal Architectures and Subsystems for Fiber Optic Space Division Multiplexing), the Fraunhofer Heinrich Hertz Institute (HHI) is researching novel, cost-efficient architectures of transceivers for simultaneous transmission in multiple spatial channels. The results will be implemented within an application-oriented demonstrator. The German Federal Ministry of Education and Research (BMBF) is funding the three-year project with a total of 2.3 million euros. Besides Fraunhofer HHI, ADVA Optical Networking SE and the Karlsruhe Institute of Technology (KIT) are involved in the project.
In the STARFALL project, the Fraunhofer HHI research groups "Submarine and Core Networks" and "Digital Signal Processing" of the "Photonic Networks and Systems" department are developing tools to plan and control optical networks with space division multiplexing, or "SDM networks". Furthermore, they will put the digital signal processing algorithms designed in the project to the test by conducting a practical experimental validation using a real-time SDM demonstrator.
Optical technologies with space division multiplexing enable increased capacity in data transmission, thus forming the backbone of the digitized world. Fueled by data-driven applications as well as high-performance mobile technologies such as 5G and soon 6G, capacity in metro and core networks is expected to grow to a total of more than 1.5 Pbit/s by 2030. To meet these and future requirements, space division multiplexing, i.e. parallel transmission via independent single fibers as well as new types of multimode and multicore fibers, will enable the urgently needed leap in network capacity.
The major advantage of SDM lies in the linear scaling of capacity with the number of spatial paths used. Record-breaking SDM experiments have already shown data transmission rates of more than 10 Pbit/s over a multicore fiber. From an economic point of view however, the current terminal realizations are not practicable for a high number of SDM channels, for example regarding power consumption and data throughput in digital signal processing. As a result, research into terminals for SDM systems is still ongoing. No industry standard exists for them to date.
The researchers in the STARFALL project are developing an innovative and energy-efficient terminal architecture using cross-channel subsystems at the optical level for the first time. This is achieved by using a monolithically integrated laser comb as the transmitting "optical power supply" and SDM-optimized super-channel reception schemes as well as cross-channel digital signal processing as the receiver. This is where researchers use cooperating function blocks with variable information exchange between data channels. At the same time, the optical and digital subsystems cooperate more efficiently, for example by exploiting the properties of the coupled comb laser lines during digital signal processing, minimizing the computational effort required per clock cycle.
The specific objectives of Fraunhofer HHI's research activities include, on the one hand, the investigation and development of Machine Learning (ML) assisted solutions to perform Quality of Transmission (QoT) estimation in SDM networks. Transfer learning will be also investigated to evaluate its benefits for knowledge sharing between conventional SSMF-based networks and SDM networks. On the other hand, the researchers will analyze and evaluate methods of SDM-optimized digital signal processing with respect to real-time implementations and further develop them into a real-time SDM demonstrator.
The practical demonstrations planned by Fraunhofer HHI in the STARFALL project represent an important milestone for the practical development aimed at the successful implementation of highly efficient fiber-optic SDM systems in optical metro and core networks. They pave the way for the widespread use of transmission systems based on space division multiplexing, thus preventing capacity bottlenecks and high-energy consumption in future data-intensive applications.