SBIR-STTR Award

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from enabling self-evolving telecommunication networks to ensure that reliable and high-speed internet access is available in large metropolitan areas and mission critical applications in smart cities will receive guaranteed Quality of Service, while the capital and operational costs of the networks are reduced. Furthermore, this technology will reduce the energy consumption of telecommunication networks by moving resources where and when they are needed, avoiding over-provisioning and waste in idle resources. This Small Business Innovation Research (SBIR) Phase I project develops a first of its kind novel Artificial Intelligent-based network performance and demand prediction platform to guarantee 5G connectivity in metropolitan areas and eventually in smart cities. With 68% of the world population living in urban areas by 2050, constant movement of people and diversity in 5G applications network requirements, network optimization is critical. However, achieving optimal network configuration requires accurate prediction of future network demand. The proposed research will utilize the external contextual data of mass human movement and their activity along with a portfolio of machine learning methodologies to perform accurate network demand prediction and consequently optimal resource allocation. The main objective of this project is to develop and deploy an automated cloud-based software that performs prediction on network key performance indicators in urban areas up to seven days in advance. This software solution enables network operators to identify and anticipate accurate temporal and spatial demands and anomalies, understand the factors that will cause demand variations, and pinpoint future opportunities for optimization based on this information. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to ensure accessible, reliable, high-speed internet. Operators spend $350 B annually on network upgrades, but only an estimated 75% of this is effective. This project will help improve the efficiency of upgrades by providing hyper-local information about network demand as well as forecasting future needs. This can be applied both to upgrading current networks and deployment of future 5G networks, and it improves energy efficiency by aligning resources with needs. This technology will enable ongoing and improved operation in fields ranging from education, emergency responders, government work, and corporate activities during the COVID-19 pandemic and the associated social distancing. This Small Business Innovation Research (SBIR) Phase II project will develop a novel prediction platform for efficient long-term planning of 4G and 5G mobile networks. This project will develop a platform that can accurately forecast network usage and behavior based on key performance indicators and external contextual data. The platform will provide accurate data regarding network demand at the micro-scale, localized by individual cell sites and frequency bands; this will enable better capacity optimization (i.e., when, where, how much).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.