ML-driven adaptive signal processing module for radio systems
This technology uses machine learning to automatically optimize how a radio device processes wireless signals in real time. The system watches how an incoming radio signal looks after it passes through the radio's internal processing stages, compares those observations to a history of past performance, and then adjusts the radio's settings to improve signal quality. Over time, the machine-learning model learns which settings work best under different conditions and updates the radio's behavior accordingly. The result is a self-tuning radio that adapts to changing signal environments without human intervention.
What you could build
An adaptive radio firmware or software module that telecom equipment makers or military radio vendors embed in base stations, software-defined radios, or IoT gateways to automatically optimize signal reception. Primary buyers would be wireless infrastructure OEMs and defense communications primes.
Who in Virginia should care
Virginia-based defense contractors and the dense Northern Virginia telecom and government communications sector would be natural licensees or co-development partners.
Readiness: Prototype likely
Concept — described but not yet demonstrated. Lab validated — supported by experimental results in the patent. Prototype likely — the text describes a built, working embodiment.
Readiness is inferred from the patent text, not from a lab visit.
The record
- Inventors
- —
- Granted
- August 27, 2019
- Status
- Granted patent
- Patent number
- 102823
Ready to talk?
Virginia Tech Intellectual Properties handles licensing for this technology.
Prosim summaries are generated from public patent text and are not legal advice.