Customer Reviews in Spectrum: Recommendation System in Cognitive Radio Networks

A recommendation system is proposed to enhance the efficiency of spectrum access in cognitive radio networks by letting secondary users broadcast the indices of channels they have successfully accessed. The probabilities of different actions, i.e. which recommendation to take or access an unrecommended channel, could be either fixed and adjustable. For the constant probability case without retransmission, an upper bound of the average number of recommendations is obtained. For the constant probability case with and without retransmission, the system is modeled as a Markov random process and the corresponding state transition probabilities are obtained. For the adjustable probability case, the anytime multi-armed bandit technique is used to adapt the strategies to environments and a performance lower bound is obtained. Numerical simulation results demonstrate that the proposed recommendation system can effectively orient the channel selections and significantly improve the performance of cognitive radio networks.