Designing, developing, and disseminating a community platform called 3DML, for facilitating the development of ML-based innovations for next-generation wireless networks and mobile applications

The ever-increasing complexity of wireless networks and their emerging applications (such as autonomous cars, virtual reality, and e-health) have spurred a significant demand to develop machine learning (ML) - empowered, intelligent network management and optimization. However, there are still two main barriers to unleashing such innovations: (i) ML-based approaches require many large labeled datasets, which are difficult to acquire in the wireless context due to both privacy and cost challenges; and (ii) the challenge of deploying complex ML models into resource-constrained wireless devices.

3DML, an open-source community platform, addresses both problems through embedded machine learning and large-scale wireless research platforms. 3DML will be the first platform, designed from the ground up, to meet the urgent need of exploring ML-based innovations for wireless applications.

The project will develop three integrated key components: i) The development of 3DML-Data will enable the collection of unprecedentedly diverse labeled datasets, ii) the design of 3DML-Client, which consists of automated tools and compression libraries to enable the development and deployment of efficient ML models, and iii) the development of a 3DML-Infrastructure, which will use both of the previous components to generate efficient ML algorithms deployed into wireless infrastructure.

Overall, 3DML will open up a host of new possibilities for developing innovations towards next generation intelligent wireless networks, including enhanced mobile broadband, massive Internet-of-things and ultra-low-latency applications in order to support emerging applications.