Soft Detection with Linear Precoding for Spatial Multiplexing Systems

We present a precoded reduced-complexity soft detection (PRCSD) algorithm for spatial multiplexing systems. The linear operations at both transmit and receive sides based on complex Householder transform convert the multi-input multi-output (MIMO) channel to be multiple-diagonal, spatially partial-response-like, so that error propagation is alleviated when applying RCSD at the receiver. The transform results in unitary precoding and feedforward matrices so that neither transmit power boost nor noise enhancement is present. Performance analysis based on pairwise error probability (PEP) shows that PRCSD achieves higher diversity advantage than existing precoding and multiple-beamforming schemes, which basically attempt to transmit signals through diagonal independent sub-channels and thus may suffer diversity loss. PRCSD can achieve full diversity as ML detection in some scenarios while reducing complexity significantly