Relay Selection Based on Bayesian Decision Theory in Cooperative Wireless Networks

Wireless networks use relay nodes as cooperative nodes to gain maximum diversity. Relay selection is one of the key challenging problems in multiuser wireless cooperative networks. This paper addresses the selection problem of the relay node and proposes posterior probability-based relay node selection methods. In these methods, all calculations are derived by either source or destination, consider both amplify-forward and decode-forward methods, and apply Bayesian decision theory to select the relay node. In the source-based method, each source node considers all the relay nodes' channel information to estimate posterior probability using Bayes theorem, whereas in the destination-based method, the destination node considers all source node channel information to calculate posterior probability. Numerical results show that our proposed relay assignment methods maximize the overall data rate of the networks and work well independently of the number of relay nodes or source-destination pairs in the network.