Collaborative Research: CNS Core: Small: Adaptive Smart Surfaces for Wireless Channel Morphing to Enable Full Multiplexing and Multi-user Gains

The connectivity solutions need to scale up massively to support unprecedented exponential growth in data rates and the number of devices. The primary approach to meet the demands has been to upgrade the infrastructure, such as adding base stations with multiple antennas and/or upgrading clients. Unfortunately, these approaches have fallen short of their goal as in practice, the channels between users and base stations have limited scattering or richness to enable spatial multiplexing, and users are not sufficiently separated in the spatial domain.

This proposal will shape the channel to unlock the full potential of wireless networks without requiring updating the base station or user device at a low cost in terms of power and expense. The proposed research aims to adaptively modify and morph the wireless medium using smart passive reflector surfaces to materialize the spatial multiplexing gains.

The underlying idea is to use smart reflectors to create additional channel diversity to manipulate the received signal before reflecting it to minimize interference at the receivers. The research brings together PIs and techniques from communications theory, networked system design, and antenna design to build scalable and low-cost wireless networks.

The project also proposes a synergistic educational and outreach plan that leverages the technical work to build exciting demos for undergraduate and K-12 classrooms. For example, a smart surface-based demo, which increases the data rate and coverage of current Wi-Fi devices, will introduce students to the wonders of engineering in a pragmatic yet compelling way, with the hope of increasing diversity in STEM-related education environments.

The proposal would develop smart surface designs capable of morphing the channel, and develop the hardware prototype and algorithms to provide coverage and multiplexing gains to support massive numbers of users and the exponential increase in data rates. The designed smart surface with fine-grained control would allow us to morph the wireless channel or environment to increase the diversity and multiplexing gains as deemed necessary during optimization.

We further establish smart surface placement theory and algorithms and quantify the performance-size trade-offs. We develop low-overhead channel estimation and low-latency optimization algorithms for the base station to support temporal channel changes and improve the data rate and connectivity. The proposed effort would develop the theory and algorithms for multi-user setups to ensure scalability with smart surfaces.

The proposed work would enable the first low-cost, practical smart surface and algorithms supporting high-mobility users with significant data-rate improvements.

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.