Hybrid ML-MMSE adaptive multiuser detection based on joint channel estimation in SDMA-OFDM systems

Abstract

Multiuser Detection (MUD) and Channel Estimation techniques in Space-Division Multiple Access aided Orthogonal Frequency Division Multiplexing (SDMA-OFDM) systems recently received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean-squared error (MMSE) MUD exhibit poor performance even though it achieves lower computational complexity. In this paper, Hybrid ML-MMSE adaptive multiuser detection based on joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method has good performance close to optimal ML performance at low SNR values and a low computational complexity at high SNR values.