NASA SBIR 2020-I Solicitation

Proposal Summary


PROPOSAL NUMBER:
 20-1- H9.07-6063
SUBTOPIC TITLE:
 Cognitive Communication
PROPOSAL TITLE:
 Cross-Layer Wide-Band Cognitive Communications Architecture Enabled by Intelligent Direct Digital Transceiver (CLAIRE)
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
AiRANACULUS
9 Flint St.
Chelmsford, MA 01824
(404) 819-0314

Principal Investigator (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
Dr. Apurva Mody
E-mail:
apurva.mody@airanaculus.com
Address:
9 Flint St. Chelmsford, MA 01824 - 2226
Phone:
(404) 819-0314

Business Official (Name, E-mail, Mail Address, City/State/Zip, Phone)

Name:
Dr. Apurva Mody
E-mail:
apurva.mody@airanaculus.com
Address:
9 Flint St. Chelmsford, MA 01824 - 2226
Phone:
(404) 819-0314
Estimated Technology Readiness Level (TRL) :
Begin: 2
End: 5
Technical Abstract (Limit 2000 characters, approximately 200 words)

AiRANACULUS, Northeastern University and NWRA supported by DRAPER propose an innovative Cross-layer Wide-Band Cognitive Communications Architecture Enabled by Intelligent Direct Digital Transceiver (CLAIRE) to meet the NASA's Space Communication and Navigation (SCaN) needs to increase mission science data return, improve resource efficiencies for NASA missions and communication (Comms) networks and ensure resilience in the unpredictable space environment. The CLAIRE cognitive system is envisioned to sense, detect, adapt, and learn from its experiences and environment to optimize the Comms capabilities for the user mission of the network infrastructure. Our Comms Node will reduce both the mission and network operations burden. This will entail research and development of Cross-layer Sensing (CLS) and the CLAIRE Decision Engine (CDE) which uses machine learning over short term and long term along with game theoretic decision to define the strategy and technique to mitigate the interference and restore the network performance. The CLS consists of RF sensing and Cyclostationary-Signal Processing analysis, Cross-layer Feature Extraction and Environment Characterization and Pattern Classification Modules. The CDE consists of the Long-term Response Engine which is driven by the Game-theoretic approaches, and the Rapid Response Engine, which is driven by Deep Reinforcement Learning (DRL) techniques. We propose to use of Supervised DRL Model Selection and Bootstrap for rapid bootstrapping. Finally, we also propose to conduct research into new state-of-the-art Direct Digital Transceiver (DDTRX) Technologies for potential application for NASA’ s mission. Latest advances in the DDTRX Technology provide sampling rates of 64 Gsps, instantaneous bandwidths of 20 GHz with four coherent channels and 8-bits per sample of quantization. This allows us to use any spectrum from VHF/UHF to Ku/ Ka Band on a single radio which will reduce the SWAP and could be of great interest to NASA.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

CLAIRE allows NASA to combine the advanced Cognitive Cross-layer Optimization with the latest breakthroughs in the Direct Digital Transceiver (DDTRX) technology. We anticipate CLAIRE to benefit the following applications: (1) Cross-layer approaches for optimum communication (Comms) (2) Efficient use of lunar Comms spectrum and interference mitigation (3) Integrated wide-band sensing and narrow-band Comms on the same radio. (4) Implementation of artificial intelligence and machine learning techniques on SWaP-constrained platforms (5) Lower SWAP.

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

Potential Non-NASA Applications include: (1) Commercial 5G and Next G communications, (2) Military cognitive communications (3) wide-band sensing and signals intelligence (4) Radar and LIDAR Applications for motion and proximity detection (5) Cross-layer optimization (6) Machine learning on large data sets etc. 

Duration: 6

Form Generated on 06/29/2020 20:58:40