Using an RTL-SDR to help Build Dynamic Spectrum Access Prototypes + DARPA Spectrum Collaboration Grand Challenge

Over on YouTube user Andre Puschmann has uploaded video showing his experiments with implementing dynamic spectrum access. Dynamic spectrum access is a upcoming technology that will allow the frequency spectrum to be more easily shared between many users. An IEEE paper describes Dynamic Spectrum Access in the following paragraph

Dynamic spectrum access is a new spectrum sharing paradigm that allows secondary users to access the abundant spectrum holes or white spaces in the licensed spectrum bands. DSA is a promising technology to alleviate the spectrum scarcity problem and increase spectrum utilization.

In his experiments Andre uses USRP and bladeRF software defined radios as the transmit radios, and an RTL-SDR as the receive radio. His video shows a video stream being received by the RTL-SDR which is not impacted by any spectrum frequency switches.

In addition to this, DARPA has recently announced a new Grand Challenge that will focus on Spectrum Collaboration. We would expect SDR’s to be heavily used in this type of challenge. Their press release writes:

DARPA today announced the newest of its Grand Challenges, one designed to ensure that the exponentially growing number of military and civilian wireless devices will have full access to the increasingly crowded electromagnetic spectrum. The agency’s Spectrum Collaboration Challenge (SC2) will reward teams for developing smart systems that collaboratively, rather than competitively, adapt in real time to today’s fast-changing, congested spectrum environment—redefining the conventional spectrum management roles of humans and machines in order to maximize the flow of radio frequency (RF) signals. DARPA officials unveiled the new Challenge before some 8000 engineers and communications professionals gathered in Las Vegas at the International Wireless Communications Expo (IWCE).

The primary goal of SC2 is to imbue radios with advanced machine-learning capabilities so they can collectively develop strategies that optimize use of the wireless spectrum in ways not possible with today’s intrinsically inefficient approach of pre-allocating exclusive access to designated frequencies. The challenge is expected to both take advantage of recent significant progress in the fields of artificial intelligence and machine learning and also spur new developments in those research domains, with potential applications in other fields where collaborative decision-making is critical.