Decentralized transceiver optimization for multi-relay aided multiuser MIMO networks

In this paper,the decentralized transceivers and corresponding channel state information(CSI)signaling concepts are proposed for weighted sum rate(WSR)maximization,via linear downlink transceiver optimization in multi-relay aided multiuser multiple-input multiple-output(MIMO)networks.Three decentralized algorithms are proposed with the local CSI requirements at the base station(BS)and the relay nodes.In the first proposed algorithm,the generalized channel inversion precoding is used at the BS to avoid the second hop channel sharing requirements among the relay nodes,and decentralized transceiver optimization of the relay nodes and users are developed to maximize the WSR.A minimum mean square error(MMSE)-based enhanced method is proposed as well.To further improve the performance,we provide a novel structure of the precoding matrix of the BS.The decentralized joint BS,relay and user transceiver optimization problem is formulated and solved.Also,the CSI signaling and decentralized processing in the time division duplex(TDD)system are analyzed.Simulation results show the effectiveness of the decentralized transceiver design compared to the existing algorithms.