AI-optimized MIMO encoder-decoder for next-gen wireless
This technology uses machine learning to dramatically improve how data is transmitted and received across wireless networks with multiple antennas, known as MIMO systems. Instead of relying on hand-engineered rules for encoding and decoding signals, it trains a neural network to jointly optimize both the transmitter and receiver ends simultaneously — essentially letting AI figure out the best way to send and recover information through a noisy wireless channel. The system works by comparing what was sent to what was received, using that error signal to continuously improve the neural network's performance. The result is a communication system that can adapt to complex, real-world channel conditions that traditional methods struggle with.
What you could build
A software-defined radio or chipset firmware layer using AI-optimized MIMO coding for next-generation wireless base stations or devices; telecom equipment vendors, chipmakers, and defense communications contractors would be the primary buyers.
Who in Virginia should care
Northern Virginia's dense concentration of defense contractors and federal telecom agencies — including those supporting DoD and intelligence community secure communications — would be natural partners or licensees.
Readiness: Lab validated
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
- May 28, 2019
- Status
- Granted patent
- Patent number
- 102829
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.