Iterative receivers for interference cancellation and suppression in wireless communications

Abstract The performance of conventional receivers for wireless communications may severely deteriorate in the presence of unaccounted interference. The effectiveness of methods for mitigating these effects greatly depends on the knowledge that is available about the interference and signal-of-interest (SOI), therefore making the design of robust receivers a great challenge. This thesis focuses on receiver structures for channel coded systems that exploit different levels of knowledge about the SOI and interference in an iterative fashion. This achieves both robustness and overall performance improvement compared to non-iterative receivers. Code division multiple access (CDMA) and spatial division multiple access (SDMA) systems are considered. The overlay of a turbo coded direct-sequence spread-spectrum (DS-SS) system and strong digitally modulated tone interference is studied. An iterative receiver, which is capable of blind cancellation of both wideband and narrowband interference is proposed based on the adaptive self-reconfigurable -filter scheme. Asymptotic performance analysis of the iterative receiver shows that significant iteration gains are possible if the signal-to-interference-plus-noise-ratio (SINR) is relatively large and the processing gain (PG) of the SOI is relatively small. Robust diversity detection in turbo-coded DS-SS system with statistically modeled interference is studied. A non-parametric type-based iterative receiver that estimates the probability density function (PDF) of interference-plus-noise is proposed. Its performance is shown to be rather robust to the number of interferers and their distances from the victim receiver and very similar to the performance of a clairvoyant receiver. Amazingly, this is achievable with no prior knowledge about the interference parameters. Furthermore, iteration gain is shown to significantly reduce the length of the pilot sequence needed for the PDF estimation. A family of iterative minimum-mean-squared-error (MMSE) and maximum-likelihood (ML) receivers for convolutionally and space-time coded SDMA systems is proposed. Joint iterative multiuser-detection (MUD), equalization and interference suppression are proposed to jointly combat co-channel interference (CCI), inter-symbol-interference (ISI) and unknown CCI (UCCI) in broadband single-carrier systems. It is shown that both in convolutional and space-time coded systems the ISI and CCI interference can be completely eliminated if UCCI is absent. This is achievable with a number of receive antennas equal to the number of users of interest and not to the total number of transmit antennas. In case UCCI is present, the effectiveness of CCI and ISI cancellation and UCCI suppression depends on the effective degrees of freedom of the receiver. Receiver robustness can be significantly preserved by using hybrid MMSE/ML detection for the signals of interest, or by using estimation of the PDF of the UCCI-plus-noise. A low complexity hybrid MMSE/ML iterative receiver for SDMA is proposed. It is shown that its performance is not significantly degraded compared to the optimal ML receiver. Its sensitivity to spatial correlation and a timing offset is assessed by using field measurement data. It was shown that the hybrid MMSE/ML receiver is robust against spatial correlation. The sensitivity to the timing offset is significantly reduced if the receiver performs UCCI suppression