Accession Number:

AD1107855

Title:

Deep Learning Collaborative Radios - Team Zylinium Phase 3

Descriptive Note:

Technical Report,01 Jan 2017,31 Jan 2020

Corporate Author:

EMBEDDED INTELLIGENCE RESEARCH LLC Gaithersburg United States

Personal Author(s):

Report Date:

2020-09-01

Pagination or Media Count:

53.0

Abstract:

Refined both the core radio features in our radio with more granular erasure coding and a more flexible MAC with dynamic slot reallocation and FDMA, as well as the reasoning components of the radio that control when we change our operating state to attempt more points and hog more spectrum. Demonstrated flawless co-existence with both active and passive incumbents. It is encouraging to be part of the scientific process while also working to build technology that is truly useful. We plan to participate in the POWDER follow on exercises to further flush out the applicability of our technology.

Subject Categories:

  • Radio Communications
  • Computer Systems Management and Standards
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE