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AWGER: ADAPTIVE WAVEFORM GENERATION FOR EXTREME RF

Solicitation ID: FA8750-22-S-7006

Agency: AFRL/Information Directorate

Type: Presolicitation
Deadline: 2027-09-30T17:00:00 ET
Eligibility: Maybe (Dual Approval Required)
Funding: Total funding of approximately $49.9M. Individual awards will normally range from $300K to $3M.
Doc Type: BAA
Clearance: Top Secret
Program Manager: Gerard Wohlrab
Last Updated: 2025-11-24 13:05
Analyzed File: BAA 22-06 Amend 8 third repub 2025.docx

Eligibility Reasoning

Federally Funded Research and Development Centers (FFRDCs) ... are subject to applicable direct competition limitations and cannot propose to this BAA in any capacity unless they meet the following conditions: FFRDCs must clearly demonstrate that the proposed work is not otherwise available from the private sector; and FFRDCs must provide a letter on official letterhead from their sponsoring organization citing the specific authority establishing their eligibility to propose to Government solicitations and compete with industry... This information is required for FFRDCs proposing to be prime contractors or sub-awardees.

Note: This is an AI-generated summary...

Summary

The Air Force Research Laboratory (AFRL) is soliciting research for the 'Adaptive Waveform Generation for Extreme RF' (AWGER) program (BAA FA8750-22-S-7006). This initiative seeks to develop technologies for cognitive waveform generation, network control, and analysis within a unified evaluation environment. Key technical areas include using machine learning to build and adapt waveforms in response to dynamic radio frequency (RF) environments, managing network throughput, coordinating physical layer changes between nodes, and ensuring resiliency against adversarial attacks. The program aims to culminate in an integrated, over-the-air demonstration combining virtual and physical nodes. The total estimated funding is approximately $49.9M through FY27, with individual awards typically ranging from $300K to $3M over 36 months. This is a two-step BAA, requiring white papers as initial submissions.

Overall Technical Areas

Cognitive Waveform GenerationMachine Learning TechniquesDigital Signal ProcessingRF Environment SimulationPhysical (PHY) Layer SimulationWaveform EvaluationAdversarial Attack ResiliencyNetwork Control and AnalysisNetwork Throughput AnalysisPHY Layer Network CoordinationNetwork Layer SimulationUnified Scenario EvaluationOver-the-Air DemonstrationSystem Integration & Test

Probable LBNL Areas

BSACSAEESAESAETALDPSA

Focus Areas

Example Priorities:
  • Machine learning or other cognitive techniques for building waveforms from fundamental digital processing blocks
  • Adjustment to waveforms based on varying radio frequency (RF) environments and interference
  • Resiliency to adversarial attacks
Specific Technical Skills:
Machine LearningCognitive RadioDigital Signal ProcessingWaveform DesignRF EngineeringInterference MitigationAdversarial AIElectronic Warfare
Potential PIs for this Area:
NameScoreOrganization
Stijn (Stan) Wielandt0.69EESA | EG | Geophysics Dept
John Wu0.69CSA | Scientific Networking (ESNET) | Tech Adv and Engagement
Marcos Lopez de Prado0.68CSA | SciData | Data Science Research
Oluwamayowa Amusat0.68CSA | SciData | Data Science Applications
Neel Rajeshbhai Vora0.68PSA | ATAP | BACI
Yilun Xu0.68PSA | ATAP | BACI
Zhe Bai0.68CSA | AMCR | Computer Science
Gazi Mahmud0.68BSA | Environmental Genomics & Systems Biology | Molecular Ecosystems Bio
Alexander Sim0.68CSA | SciData | Data Science Research
Xiaoya Chong0.67ESA | ALS | PS Computing staff
Example Priorities:
  • Network throughput analysis and control within varying RF environments
  • Coordination/handshaking of PHY layer changes between nodes in a network/neighborhood
  • Network layer simulation and network control evaluation
Specific Technical Skills:
Network AnalysisPHY Layer ProtocolsNetwork SimulationDistributed SystemsSoftware-Defined NetworkingThroughput OptimizationMobile Ad Hoc Networks (MANETs)
Potential PIs for this Area:
NameScoreOrganization
Anand Krishnan Prakash0.69ETA | Building Technology & Urban Systems | Bldg Technologies Dept
Georgios Michelogiannakis0.69CSA | AMCR | Computer Science
Alexander Sim0.69CSA | SciData | Data Science Research
Vinay Sawal0.69CSA | NERSC | Data Center Department
Dan Bonachea0.68CSA | AMCR | Computer Science
Angelos Ioannou0.68CSA | AMCR | Computer Science
John Wu0.68CSA | Scientific Networking (ESNET) | Tech Adv and Engagement
Stijn (Stan) Wielandt0.68EESA | EG | Geophysics Dept
Inder Monga0.68CSA | Computing | Scientific Networking (ESNET)
Alexandre Moreira da Silva0.68ETA | ESDR | Energy Storage & Dist Dpt
Example Priorities:
  • RF environment / physical (PHY) layer simulation and designed waveform evaluation
  • Unified scenario evaluation environment
  • Over the air demonstration consisting of virtual nodes from emulation and physical nodes
  • Integrated demonstration of both network control and waveform generation
Specific Technical Skills:
System IntegrationModeling and SimulationTest and EvaluationEmulationVirtualizationOver-the-Air (OTA) TestingHardware-in-the-Loop (HIL)Scenario Development
Potential PIs for this Area:
NameScoreOrganization
Gregory Lemieux0.70EESA | CESD | Earth System Sciences
Douglas Black0.70ETA | ESDR | Energy Storage & Dist Dpt
Cynthia Regnier0.69ETA | Building Technology & Urban Systems | Whole Building Sys Dept
David Blum0.69ETA | Building Technology & Urban Systems | Bldg Technologies Dept
Zachary Needell0.69ETA | Energy Analysis & Environmental Impacts | Sustainable Energy Dept
Alexander Sim0.69CSA | SciData | Data Science Research
Alexandre Moreira da Silva0.68ETA | ESDR | Energy Storage & Dist Dpt
Jessica Granderson0.68ETA | Building Technology & Urban Systems
Michael Wetter0.68ETA | Building Technology & Urban Systems | Bldg Technologies Dept
Shawn Tornga0.68LD | LD | ONHS

Potential LBNL PIs (Overall)

Note on PI Matching: These suggestions are generated through an AI-driven semantic analysis of LBNL staff profiles.

NameScoreOrganization
Alexandre Bayen0.76ETA | Energy Analysis | Systems & Energy Tech Analysis · Network Control and Analysis
Satyarth Praveen0.75CSA | SciData | Data Science Applications · Machine Learning Techniques
Stijn (Stan) Wielandt0.73PSA | Engineering | Electronic Engineering · RF Environment Simulation
Daniel Arnold0.73ETA | ESDR | Energy Storage & Dist Dpt · Adversarial Attack Resiliency
Arpit Gupta0.73CSA | ESNET | Tech Adv and Engagement · Network Throughput Analysis
Prabal Dutta0.73ETA | Building Tech. & Urban Sys. | Bldg Technologies Dept · PHY Layer Network Coordination
Han Lee0.73PSA | Engineering | Electronic Engineering · System Integration & Test
Bruce Mah0.73CSA | ESNET | Tech Adv and Engagement · Network Layer Simulation
Edward Nichols0.72EESA | EG | Geophysics Dept · Waveform Evaluation
Gregory Lemieux0.72EESA | CESD | Earth System Sciences · Unified Scenario Evaluation

Fundamental Research Exemption (FRE)

As of the date of publication of this BAA, the Government cannot identify whether work proposed under this BAA may be considered fundamental research and may award both fundamental and non-fundamental research. Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to select award instrument type and to negotiate all instrument terms and conditions with selectees. Appropriate clauses will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate.