RF spectral convergence is a novel system design paradigm that prioritizes increased cooperation between RF systems and utilizing RF energy (or waveforms) for multiple applications. This paradigm increases spectral efficiency, reliability, and system capabilities when compared to current 'stovepiped' systems. Multi-function systems are critical to the realization of RF convergence systems. We have previously demonstrated single-platform systems that simultaneously enable communications, radar, positioning, navigation, and timing (PNT) and other RF capabilities. There are many roadblocks preventing the deployment of such systems, one of which is the lack of flexible, capable back-end processors; multi-function systems require hardware capable of performing extremely complex computations efficiently, while also being flexible enough to cover a wide range of functionality. In this paper, we discuss the DASH SoC in the context of RF spectral convergence. This revolutionary, heterogeneous SoC design framework enables the development of such flexible and powerful hardware. We demonstrate through simulations that using the DASH SoC increases performance of a joint-radar communications receiver, a miniature RF convergence system.

Original languageEnglish (US)
Title of host publication56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Number of pages8
ISBN (Electronic)9781665459068
StatePublished - 2022
Event56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 - Virtual, Online, United States
Duration: Oct 31 2022Nov 2 2022

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393


Conference56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Country/TerritoryUnited States
CityVirtual, Online


  • Heterogeneous SoC
  • Navigation
  • Position measurement
  • Radar
  • Spectral convergence
  • Spectrum sharing
  • Timing
  • Wireless communications

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications


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