2010 Qualcomm Cognitive Radio Competition
While detecting digital television signals using the ATSC (American standard for digital television broadcasting) is not a big deal (given their embedded pilot tones), detecting 200 KHz wide wireless microphone signals with the detection performance required by the FCC proposal becomes a challenge. Qualcomm provided the different teams with training data, consisting on both signal sets with a wideband of 6 MHz and information on the frequencies where microphone signals were located. Contestants had to use this data to find a fitting model for the microphone signals and develop algorithms to detect them. The algorithm was judged based on its performance, novelty and implementation complexity.
The approaches followed by the 14 participating teams were fairly different. For example, the ECE Virginia Tech team:
"The students developed a fairly robust solution. They determined a baseline noise correlation matrix from a data set with no wireless microphone signals. To see if a signal is present in a new environment, they compare the new correlation matrix with the baseline matrix using singular value decomposition. If their algorithm determines there is a signal, it calculates the center frequency from the measured auto correlation of the signal."
The winning team (ECE Illinois), advised by V. V. Veeravalli, commented that the key problem was learning to distinguish wireless microphone signals from narrowband interference caused by other electrical devices. They addressed this problem by characterizing the unique features of this narrowband interference.
Congratulations to the winners!
Edit: In the CRT blog appears a link (that I missed) to a presentation by Stephen J. Shellhammer about this contest. Since it includes some technical details I decided to include it here.