Optimal weighting of soft-information in a SAGE-based iterative receiver for coded CDMA

An iterative receiver for joint multiuser-decoding and channel-estimation of coded CDMA is derived by applying the noise-splitting approach within the space alternating generalized expectation-maximization (SAGE) framework. We consider asynchronous single-rate DS/CDMA over flat Rayleigh fading channels. The resulting receiver structure comprises partial successive interference-cancellation (SIC), channel estimation, and soft-input/hard-output maximum likelihood sequence decoding (MLSD) for each user. Additionally, one obtains a set of noise-weighting coefficients that can be freely chosen within weak constraints. These coefficients determine the amount of feedback from the decoder output to the decoder input in the subsequent iteration, and thus, "how extrinsic" the decoder output values are. The noise-weighting coefficients strongly influence the system performance. Their optimization within the SAGE framework leads to extrinsic output values in most of the cases. The proposed receiver is evaluated by Monte-Carlo simulations, and it shows two major advantages: high load is supported and convergence is guaranteed.