Adaptive soft-input soft-output multiuser detection for coded CDMA systems

The optimum, and many suboptimum, soft-input soft-output (SISO) multiuser detectors require a lot of a priori information about the multiuser system, such as all users´ transmitted waveforms, timing, the channel impulse response, etc. We apply adaptive algorithms in the SISO multiuser detector in order to avoid the need for this a priori information. We propose two adaptive SISO parallel decision feedback detectors based on the normalized least mean square and recursive least squares algorithms for both synchronous and asynchronous CDMA systems, respectively. Compared with traditional non-SISO adaptive detectors, our SISO adaptive detectors effectively exploit the a priori information about coded symbols, which is based on soft inputs from a bank of single user decoders, to further improve their convergence performance. Monte-Carlo simulation results are presented and compared.