Optimal Capacity in Underlay Paradigm Based Cognitive Radio Network with Cooperative Transmission

In an underlay paradigm based cognitive radio (CR) network, due to the constraint of interference threshold, secondary users always experience low system capacity. In this paper, we propose a distributed scheme to improve the capacity of underlay based CR network where the communication between secondary users is assisted by a relay node. The relay node is characterized by channel states of all related links, and the channel state transitions is presented by finite state Markov channel. In particular, the CR network with cooperative transmission is formulated as a restless bandit system where each potential relay node acts as a bandit. With this stochastic optimization formulation, the optimal policy is determined in a distributed method. Simulation results is presented to illustrate the performance of the proposed scheme.