Cooperative relay selection policy using partially observable Markov decision process

In wireless mobile environment, the wireless channels are unreliable and change fast due to fading and users' movement. Since the wireless channel state is not directly observable at the receiver but is embedded in the received signal, this paper uses hidden Markov model (HMM) to model and predict the state of available relays, and considers relay selection as a stochastic process where the state of wireless channel varies randomly. The objective of the process is to select one relay among different alternatives in each time-slot according to their channel state information (CSI) with the goal of maximizing the long term information rate of the whole transmission period. We model the whole procedure of relay selection as a type of partially observable Markov decision processes (POMDPs), and the optimal policy of which relay will be selected at each time-slot can be acquired by solving POMDPs with dynamic programming-based hidden Markov model scheduling algorithms. Simulation results are presented to show the effectiveness of the proposed scheme.