Self-Programmable Metasurface Networks for Wireless Communications and IoT
Abstract
The requirements for next-generation wireless communications, networks and internet-of-things (IoT) have been -exponentially growing in recent years, not only in terms of data rates, but also of reliability, latency, power -consumption and massiveness. These demands have been driving new paradigms for hardware and underlying -communication protocols # yet these alone are not sufficient to support the continued growth rate. The -overarching goal of this multi- university international effort is to develop and advance the fundamental science -necessary to enable the next generation of communication networks that rely on ubiquitously distributed -intelligent metasurfaces, leveraging network complexity and social concepts to disruptively advance the relevant -performance metrics for communication and information processing. -Achieving this vision requires a holistic, cross-disciplinary approach, which combines new concepts from -electrical engineering, material science, physics, mathematics and social sciences. Our team is formed by worldleading experts in these technical areas from US and Finland, whose synergistic research efforts will synthesize -new wireless communication modes by integrating next-generation engineered metasurfaces with computers and users. -Our team will build on recent breakthroughs in the integration of: (i) active, nonlinear, programmable and timevarying elements in metasurfaces; (ii) new material platforms for the extension to higher frequencies; (iii) adhoc optimization algorithms and communication protocols to exploit these hardware advances; (iv) human-machine -interaction models integrated with hardware and algorithms to drive network design, optimization and -reconfigurability. Our synergistic effort across two continents will demonstrate metasurfaces that can selfprogram and control the communication spectrum, channel properties and scattering features with flexibility, -self-adapting to changes in the environment and users, maximizing relevant metrics of interest, sensing and -processing at low-energy and with fast speeds massive amount of data, and enabling ease of access to the users -around them. The realized systems will leverage neuromorphic operations to ensure agility, low energy -consumption, massively parallel analog-domain signal processing, embedded intelligence, and selfreconfigurability driven by human-machine interface and social science concepts. A portion of the funding will be -used to upgrade a real-time oscilloscope to mm-wave frequencies, used to test two network demonstrators that will -showcase disruptive advances in networks, hardware, software and human-machine interactions focused respectively -on indoor and outdoor environments. -Our results will broadly advance the science necessary to enable next-generation communication systems and -revolutionize communication networks and IoT, while enabling breakthroughs in material science, modulators, -metasurfaces, sensors, communication algorithms, human-machine interfaces and social sciences. This program will -also support 17 Ph.D. students and postdocs annually in joint study programs between US and Finland, providing -opportunities for workforce development at the frontiers of a highly interdisciplinary field of science, and for -intense knowledge exchanges across universities and relevant partners.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 09, 2024
- Source ID
- N000142412779
Entities
People
- Andrea Alù
Organizations
- Office of Naval Research
- Research Foundation of The City University of New York
- United States Navy