Performance of adaptive iterative multiuser parallel decision feedback with different code rates

An adaptive receiver which combines multiuser Parallel Decision-Feedback with MAP decoding in an iterative manner is presented for synchronous coded DS-CDMA. Performance with various convolutional code rates is considered. Optimal filters are derived using both Minimum Mean Squared Error (MMSE) and Least Squares (LS) criteria. When used with short (repeated) spreading codes, the adaptive LS receiver requires only a training sequence and timing for estimation of all filter coefficients. The adaptive receiver performs significantly better than the standard (soft) interference canceller, since the adaptive algorithm attempts to measure and exploit the joint statistics of the output of the MAP decoder with the input symbols. Numerical results are presented which illustrate how performance depends on the rate of the convolutional code, assuming similar decoding complexity. These results show that low code rates perform best at moderate loads and low received power. Higher code rates can achieve very low packe t error rates for an overloaded system (number of users greater than the bandwidth expansion).