NIST model targets Wi-Fi, Bluetooth sharing

NIST
Jacob Rezac uses a NIST modeling technique to find configurations that enable Wi-Fi and Bluetooth devices to share channels. (J. Coder/NIST)

Researchers at the National Institute of Standards and Technology (NIST) have come up with a new technique designed to make it easier to share spectrum.

The study involved coexistence between a Wi-Fi and a Bluetooth system operating in the same frequency bands.

The model is a result of NIST’s use of statistics to develop new tools that can meet complex challenges in enabling wireless systems to share limited spectrum, according to a press release.

Researchers said their model reduces the number of measurements needed to estimate reliable configurations by about 33%.

“We’re introducing a new method for designing communications experiments,” said co-author and group leader Jason Coder in a statement. “This new method is adaptable, meaning that it utilizes the results of past measurements on a device to inform the next set of measurements. Using current methods, I might test a device in 100 different configurations to characterize its performance. But with this new adaptable method, I might be able to achieve the same result with fewer measurements.” 

The conventional method of evaluating coexistence would be to sample virtually all possible configurations and monitor the resulting performance of both systems, the researchers explained. However, the new NIST method involves a sequential series of experiments that select transmission configurations based on a small set of previously collected coexistence data.

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Researchers simulated the experiment 50 times, using data from previous lab experiments. They needed an average of about eight measurements to identify at least 95% of configurations resulting in successful spectrum sharing, about 33% fewer than conventional testing of all configurations requiring about 12 measurements.

“The benefit to the larger community is that we may be able to significantly reduce the amount of time industry spends characterizing their devices, say for example, when they’re trying to navigate the regulatory approval process,” Coder explained. “In some cases, we are enabling them to demonstrate compliance and performance with fewer measurements. This can save time, money, and reduce the barriers for a new product to enter the market. From the research side it should be a great new tool that enables us to characterize and understand complex systems more quickly and efficiently.” 

According to NIST, the new model is expected to work for up to 10 devices operating simultaneously.

The researchers are investigating other new techniques using machine learning and artificial intelligence that they expect will scale up for larger problems.