EAGER: Biomimetic wireless system design for IoT networks: from sensors to brain controlled applications

Michigan State University, East Lansing MI

Investigators

Abstract

The Internet of Things (IoT), which networks versatile devices for information exchange, remote sensing, monitoring and control, is finding promising applications in nearly every field. Motivated by the human circulation system, this project introduces innovative methodologies that can regulate the design and analysis of future IoT networks, and provide more reliable human-device interface, including brain-controlled applications. Potentially, it can make significant contributions to the establishment of an ideal human-device platform for Smart Home, Smart Grid, health monitoring, national security, e-commerce, as well as many future applications that can benefit from fast and reliable human-device communications. Moreover, by integrating the technological advances resulting from this project into the curriculum development and outreach activities at Michigan State University, significant impacts are expected from this project on training a highly-skilled and diverse workforce in the areas of wireless communications and IoT networking. This project aims to develop a unified framework for network modeling and characterization, and to develop innovative techniques for IoT network design, management and performance evaluation, so as to enable the future human-device user interface. More specifically, this project plans to: 1) develop a unified framework to characterize the convergence of network centric management and ad hoc flexibility. The new framework includes all the existing networks as special cases, and makes quantitative network performance evaluation more tractable and systematic; 2) develop innovative network design and performance analysis methodologies based on the unified framework. Optimal topology design will be provided for throughput maximization. Stability, delay and efficiency analysis will be conducted to provide benchmarks on network performance evaluation. Diversity enhancement and dynamic routing protocol design will be carried out to reinforce network security and reliability; 3) develop innovative machine learning based overlapping user grouping techniques for massive multi-input multi-output systems. These new techniques can greatly increase the system capacity and ensure full coverage for all the IoT devices; and 4) apply the advanced tools in communications to perform multi-level computational brain analysis, and to achieve more accurate brain signal extraction. Multi-level brain analysis will result in better understanding on brain functions, dysfunctions and brain processing capacity. Accurate brain signal extraction lays the foundation for the development of reliable interface between the human mind and brain-controlled devices, which will be new members in the IoT family. Transformative research in this project includes new IoT network design, management and performance evaluation techniques, as well as the new user interface between human mind and brain-controlled devices.