Joint Channel Estimation and Multi-User Detection for SDMA OFDM Based on Dual Repeated Weighted Boosting Search

A joint channel estimation and Multi-User Detection (MUD) scheme is proposed for multi-user Multiple-Input Multiple-Output (MIMO) Space Division Multiple Access / Orthogonal Frequency-Division Multiplexing (SDMA/OFDM) systems. We design a Dual Repeated Weighted Boosting Search (DRWBS) scheme for joint channel estimation and MUD, which is capable of providing ´soft´ outputs, directly fed to the Forward Error Correction (FEC) decoder. The proposed scheme reduces the complexity of the receiver, since it integrates the channel estimation and MUD into a single module and it forwards the Log-Likelihood Ratios (LLRs) to the channel decoder. It also provides an effective solution to the multi-user MIMO channel estimation and MUD problem in ``rank-deficient´´ scenarios, when the number of users is higher than the number of receiver antennas. The simulation results demonstrate that the proposed scheme is capable of attaining a BER performace close to the ideal scenario of the Maximum Likelihood (ML) MUD associated with perfect channel knowledge.