Researchers Apply Mathematics' Matching Theory To Spectrum Crunch

By Jof Enriquez,
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Researchers at King Abdullah University of Science and Technology (KAUST) have proposed an algorithm that pairs cognitive radio network users anonymously to share valuable wireless spectrum bandwidth.

A plethora of spectrum crunch solutions are being developed as mobile data services continue to eat up finite bandwidth resources. There are only so many radio frequencies that can possibly be allocated for a growing number of users, and researchers consider spectrum sharing opportunities.

According to KAUST researchers Dr. Doha Hamza and Jeff Shamma, Professor of Electrical Engineering, a branch of game theory called matching theory can provide a viable answer, wherein two anonymous network users can pair up and share frequencies.

Matching theory is a Nobel Prize-winning mathematical framework describing the formation of mutually beneficial relationships. It was originally applied in the field of economics, but has found useful application in healthcare. It is being used successfully in kidney-paired exchange programs, and has been credited with contributing to an increase in the number of kidney transplants worldwide. Other applications include college admissions and communication networks.

A type of communication network technology that offers optimal network usage, and encourages a number of technologies like dynamic spectrum access, self-organizing networks, and spectrum markets that is helping in improving communication is cognitive radio.

The two KAUST researchers propose a cognitive radio network where secondary users (SUs) are allowed access time to the spectrum belonging to the primary users (PUs).

"Cognitive radio technology, as we call it, is a promising approach to solve the wireless spectrum scarcity problem,” explains Hamza in a news release. “This technology allows secondary unlicensed users to access the primary licensed users' frequency bands. To make this possible, the primary and secondary users need to be robustly paired in a way that ensures mutual benefit while maintaining quality-of-service constraints.”

“Primary users and secondary users need to be matched so that the partnership is mutually beneficial and binding,” adds Shamma. “Different partnerships can provide different benefits, and primary and secondary users can have preferences over possible partnerships; however, unlike conventional applications for matching theory, there is no central authority to regulate the market, meaning that primary and secondary users have limited information about the preferences of other actors.”

To compensate for the lack of central authority, the researchers propose a distributed blind matching algorithm (BLMA) where "the agents meet one-on-one and make proposals based on their current aspirations."

Shamma explained that “despite the blind encounters and limited information, we showed that this simple dynamic converges to a stable-matching state in which no pair of agents has an incentive to break their current matches in favor of others.”

The KAUST research is published in a recent edition of IEEE Journal on Selected Areas in Communications.