Channel Sensing Order for Cognitive Radio Networks Using Reinforcement Learning
This paper investigates the problem of channel sensing order used by a cognitive multichannel network, where each user is able to perform primary user detection on only one channel at a time. The sensing order indicates the sequence of channels sensed by the secondary users when searching for an available channel. When using an optimal sensing order, the secondary user can find faster a free channel with high quality. Brute-force algorithms may be used to find the optimal sensing order. However, this approach requires great computational effort.