A Two-Dimensional Multiarmed Bandit Approach to Secondary Users with Network Coding in Cognitive Radio Networks. (9th August 2015) - Qu, Yuben; Dong, Chao; Niu, Dawei; Wang, Hai; Tian, Chang
Abstract : We study how to utilize network coding to improve the throughput of secondary users (SUs) in cognitive radio networks (CRNs) when the channel quality is unavailable at SUs. We use a two-dimensional multiarmed bandit (MAB) approach to solve the problem of SUs with network coding under unknown channel quality in CRNs. We analytically prove the asymptotical-throughput optimality of the proposed two-dimensional MAB algorithm. Simulation results show that our proposed algorithm achieves comparable throughput performance, compared to both the theoretical upper bound and the scheme assuming known channel quality information.