Could Machines Help End Dropped Calls?

WEABT-header

Have you ever tried to make a phone call during a concert or big celebration, but the call wouldn't go through?

webt-dropped-calls-lead

Whether it’s dealing with the aftermath of disasters or large celebrations, our present telecommunication networks can’t always cope with the increase in communication volume.

But what if your cellphone was smart enough to find a less trafficked communication channel during a peak usage period? Or what if your tablet knew the quickest way to connect to the internet?

All communication transmissions depend on the radio spectrum, which is the radio frequency portion of the electromagnetic spectrum. This includes frequencies allocated to the mobile industry and other communication sectors over the airwaves. The spectrum available for communication airwaves is increasingly competitive as technology advancements open doors to new wireless communication applications.

test

The spectrum has a finite capacity available for its users, and the Federal Communications Commission and National Telecommunications and Information Administration must balance the needs of military, local governments, commercial entities and the general public.

In order to maintain control of the spectrum, we need systems that can quickly route telecommunication traffic, protect channels from adversaries and increase bandwidth during times of emergency.

Two Lockheed Martin engineers are on the case and applying their knowledge in machine learning to the radio frequency spectrum. 

SMARTER, FASTER SYSTEMS

Alex Lackpour and Tom Szumowski are developing smarter systems that evaluate spectrum usage and, if necessary, redirect users and operators to less trafficked channels.

“Instead of having human analysts review the spectrum for days to identify open channels, a machine can look at the spectrum usage and quickly determine how many individuals are using a channel,” Lackpour explains. “Machines can also identify where the spectrum is not being used and notify a human operator to switch channels.”

The key to this smart system is building a partnership between humans and machines. The machines search, filter and index data on a large scale, allowing humans to find patterns that might otherwise be undetected.


 

MORE FROM THE ENGINEERING EXPERTS

Alex Lackpour is a Senior Engineer at Advanced Technology Laboratories, which is on the front lines of Lockheed Martin's applied research and development efforts. 

Read more of Alex's research on the electromagnetic spectrum here.

DOWNLOAD THE WHITE PAPER

 

 

 

 

 


BANDWIDTH ON THE BATTLEFIELD

Using human-machine partnerships have opportunities beyond reducing dropped calls.

Currently, U.S. forces and allies stationed aboard are faced with a growing number of insurgent groups trying to control the spectrum with radios that cost as little as $15.

“To support use of the spectrum at home and abroad, we need smarter systems that can recognize and act more quickly than a human when spectrum needs to be shared or denied,” Lackpour explains.

RF-Spectrum_935x314_BTM

Having command of the spectrum allows U.S. forces to block enemies from using the spectrum and hinder their ability to detonate roadside bombs, organize ambushes or issue cyber attacks from a compromised system.

“We’re developing technologies that are adaptable and can learn and make changes,” Szumowski explains. “Our machine learning technology enables warfighters to detect and deny adversary signals that are otherwise hidden or difficult to jam.”  

Smarter systems help your calls go through, and keep the connections with bad or dangerous intents out, increasing the performance, speed and safety of the radio spectrum. 


YOU MIGHT ALSO LIKE...