Cognitive radio multiple access control for unlicensed and open spectrum with reduced spectrum sensing requirements

In this paper, two different multiple access control schemes with reduced sensing functions, called restricted sensing and minimum sensing, have been proposed for the application of cognitive radio in unlicensed and open spectrum bands. The schemes are developed by combining the usage of multichannel CSMA and a reinforcement learning algorithm in a distributed manner. By considering the learning experience from previous transmission, users will only sense or directly access a channel that has a higher success rate. Compared with full sensing, where the scheme senses the entire available spectrum, both schemes maintain a higher throughput performance and sense fewer channels in a low user density scenario. In a high user density scenario, restricted sensing performs equally as well as full sensing. The minimum sensing scheme delivers a slightly lower throughput, but has a significantly reduced sensing requirement compared with the other two schemes.