Source: Radio Science

Soon after the first radio communications were invented in the late 19th century, a problem arose. The growing number of broadcasters started encountering massive interference from others using the same wavelengths. Regulations such as the United States’ Radio Act of 1927 began assigning wavelengths to specific users, but the recent skyrocketing demand for bandwidth created by wireless technologies such as smartphones, satellites, and drones is fast overwhelming the finite spectrum. Now, a study from China presents a novel approach to monitoring and managing radio traffic jams using the cloud.

China has a national radio monitoring system that covers all wavelengths between 20 and 3,000 megahertz. But the system isn’t automatic and can’t collect or analyze information in real time. To address that problem, Lu et al.  proposed creating a monitoring system consisting of spectrum sensors that detect different radio wavelengths and automatically send usage data to computational architecture based in the cloud. The team built a pilot system in Hekou, a Chinese town near the Vietnamese border, installing five spectrum sensors that transmit data to an artificial intelligence–driven computing program that produces analysis for radio planning and management.

Researchers assess how sensor networks and data mining can be used to monitor radio waves
Researchers developed a prototype system and found many interesting stories hidden in big data on national security and radio usage. Credit: Lu et al. [2017]

At the time of publication, the team’s system had been running steadily for more than 6 months and had successfully detected both interference and illegal broadcasting signals, the team reports. Because radio waves do not stop at national borders, the team collected usage data on both Chinese and Vietnamese telecommunications companies. Such monitoring not only is key to national security but could allow neighboring countries to coordinate their radio usage and avoid harmful interference. (Radio Science,, 2017)

—Emily Underwood, Freelance Writer


Underwood, E. (2018), Managing radio traffic jams with the cloud, Eos, 99, Published on 07 February 2018.

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