Rural towns are usually tens of miles or even farther away from one another, and many rural towns and agriculture farms are far away from their nearest Internet backbone connection points. Thus high-capacity, long-distance wireless x-haul networks serve as important middle-mile solutions for connecting rural towns and agriculture farms with one another and with the Internet backbone. However, the existing practice has been mostly limited to microwave bands, and these microwave x-haul systems tends to have limited communication capacity. Free-space optical communications (FSOC) have been explored for high-capacity wireless x-haul networks. However, the existing practice in long-distance FSOC has been limited to inter-satellite data transfers, and terrestrial FSOC has been limited to short-distance communications between close-by buildings. To enable FSOC-based long-distance, high-capacity terrestrial x-haul networking, this project will develop robust Multi Input Single Output (MISO) FSOC systems that are expected to become foundational components of rural broadband solutions. The enabled real-time data-intensive rural applications, such as agriculture automation and XR-based rural education, are expected to have transformative impact on rural industries and communities.
The developed MISO FSOC system will leverage spatial, polarization, and wavelength diversity to mitigate the impact of beam wandering and scintillation in long-distance terrestrial FSOC, and it can be optimized for transmission distances from 1km to 10km and beyond by using different aperture sizes, spatial distances, and polarization states. This project will also develop the AraOptical 2.0 programmable networking system whose controller manages the control, monitoring, and data planes of the MISO FSOC system to optimize its operation and to integrate it into a holistic x-haul architecture. An AraOptical 2.0 link will be deployed in ARA PAWR, and, leveraging the four-season weather in Central Iowa, this project will conduct extensive measurement campaigns to investigate the behavior of MISO FSOC links together with co-located mmWave and microwave links, and it will develop machine learning models and optimal controls for MISO FSOC systems and long-distance, high-capacity x-haul networks in general. This project will generate first-of-its-kind real-world measurement data and models of long-distance FSOC systems under different weather conditions and experiment profiles, and they will serve as important tools for the broader research and education community. This project will create exciting opportunities for broadening participation in computing, and it will help enrich undergraduate and graduate research and education as well as K-12 outreach.
This project is a part of the National Science Foundation CNS RAISE program.
Project Team
- Iowa State University: Nadim Md (Ph.D. Student), Sarath Babu (Research Scientist) Daji Qiao, Hongwei Zhang (Lead PI)
- University of California – Irvine: Ozdal Boyraz (PI), Xun Li