Abstract
The optimum and many suboptimum iterative soft-input soft-output (SISO) multiuser detectors require a priori information about the multiuser system, such as the users' transmitted signature waveforms, relative delays, as well as the channel impulse response. In this paper, we employ adaptive algorithms in the SISO multiuser detector in order to avoid the need for this a priori information. First, we derive the optimum SISO parallel decision-feedback detector for asynchronous coded DS-CDMA systems. Then, we propose two adaptive versions of this SISO detector, which are based on the normalized least mean square (NLMS) and recursive least squares (RLS) algorithms. Our SISO adaptive detectors effectively exploit the a priori information of coded symbols, whose soft inputs are obtained from a bank of single-user decoders. Furthermore, we consider how to select practical finite feedforward and feedback filter lengths to obtain a good tradeoff between the performance and computational complexity of the receiver.
Highlights
Iterative soft-input soft-output (SISO) multiuser receivers for coded multiuser systems have received widespread attention since they can provide near single-user performance in a system with multiple-access interference (MAI) by iteratively combining multiuser detection and single-user decoding
We use adaptive algorithms in the iterative SISO parallel decision-feedback detector (PDFD) for asynchronous coded direct-sequence codedivision multiple-access (DS-CDMA) systems in order to avoid the need for the a priori information about system parameters, such as multiple users’ spreading codes and relative delays between users
First we presented an optimum SISO parallel decision-feedback detector for asynchronous coded DSCDMA systems, and proposed an adaptive implementation of it when all users’ signature waveforms and relative delays were unknown to the receiver
Summary
Iterative soft-input soft-output (SISO) multiuser receivers for coded multiuser systems have received widespread attention since they can provide near single-user performance in a system with multiple-access interference (MAI) by iteratively combining multiuser detection and single-user decoding. Linear iterative SISO multiuser detectors, which employ a decorrelator [7] or a minimum mean square error (MMSE) filter [8] on the output of the soft interference cancellation, significantly improve the system performance Their computational complexity is only a cubic function of the number. We use adaptive algorithms in the iterative SISO parallel decision-feedback detector (PDFD) for asynchronous coded DS-CDMA systems in order to avoid the need for the a priori information about system parameters, such as multiple users’ spreading codes and relative delays between users. For adaptive implementation of the SISO PDFD for asynchronous DS-CDMA systems, we select practical finite feedforward and feedback filter lengths to obtain a good tradeoff between the system performance and computational complexity of the receiver.
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