Polymorphic Wireless Computing for Ultra-Wideband 6G Spectrum Dominance

Abstract

Achieving technological dominance in sixth generation (6G) wireless networks is of fundamental strategic importance to the economicwell-being of the United States, its global leadership, and ultimately its long-term security. To achieve this goal, effective exploitation of extremely large bandwidths in the Terahertz (THz) spectrum will be necessary to establish Terabit-per-second communication links. On the other hand, existing computational paradigms for wireless networks are unable to function at the scale of tens of Gigahertz (GHz) per second, which ultimately makes them not applicable for 6G. Addressing this issue requires fundamental research breakthroughs that will radically change how computing will be conducted in 6G wireless systems. To this end, the proposed YIP project will lay the foundations of a new paradigm named polymorphic wireless computing (PWC). The key outcome of the YIP research will be novel techniques that will seamlessly adapt not only the underlying algorithmic structure, but also the hardware and software structure of the 6G wireless platform according to ongoing mission-driven objectives, existing network/spectrum operating conditions, and current performance metrics of interest, while being able to operate at several GHz of bandwidth. To this end, we will perform highly-interdisciplinary research at the intersection of machine learning, embedded systems, wireless networking and wireless security. Our research will include the design of highly-innovative algorithms based on distributed neural networks, dynamic neural architecture search (DNAS) and dynamic network pruning (DNP) to achieve the right trade-off between computational complexity, flexibility and performance. To reduce our research to practice, we will (i) prototype our PWC-based techniques on software-defined radio platforms equipped with reconfigurable hardware; and (ii) leverage unique state-of-the-art facilities such as the ONR DURIP-funded THz testbeds at Northeastern University to perform extensive experimental evaluation in realistic use-case scenarios.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 06, 2023
Source ID
N000142312221

Entities

People

  • Francesco Restuccia

Organizations

  • Northeastern University
  • Office of Naval Research
  • United States Navy

Tags

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks