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.

Orientadores: João Marcos Travassos Romano, Francisco Rodrigo Porto Cavalcanti / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T00:19:46Z (GMT). No. of bitstreams: 1 Cavalcante_CharlesCasimiro_D.pdf: 8652621 bytes, checksum: bf432c4988b60a8e2465828f4f748b47 (MD5) Previous issue date: 2004 / Resumo: Esta tese é dedicada ao estudo de tecnicas de separação cega de fontes aplicadas ao contexto de processamento multiusuario em comunicações digitais. Utilizando estrategias de estimação da função de densidade de probabilidade (fdp), são propostos dois metodos de processamento multiusuario que permitem recuperar os sinais transmitidos pela medida de similaridade de Kullback-Leibler entre a fdp dos sinais a saida do dispositivo de separação e um modelo parametrico que contem as caracteristicas dos sinais transmitidos. Alem desta medida de similaridade, são empregados diferentes metodos que garantem a descorrelação entre as estimativas das fontes de tal forma que os sinais recuperados sejam provenientes de diferentes fontes. E ainda realizada a analise de convergencia dos metodos e suas equivalencias com tecnicas classicas resultando em algumas importantes relações entre criterios cegos e supervisionados, tais como o criterio proposto e o criterio de maxima a posteriori. Estes novos metodos aliam a capacidade de recuperação da informação uma baixa complexidade computacional. A proposição de metodos baseados na estimativa da fdp permitiu a realização de um estudo sobre o impacto das estatisticas de ordem superior em algoritmos adaptativos para separação cega de fontes. A utilização da expansão da fdp em series ortonormais permite avaliar atraves dos cumulantes a dinamica de um processo de separação de fontes. Para tratar com problemas de comunicação digital e proposta uma nova serie ortonormal, desenvolvida em torno de uma função de densidade de probabilidade dada por um somatorio de gaussianas. Esta serie e utilizada para evidenciar as diferenças em relação ao desempenho em tempo real ao se reter mais estatisticas de ordem superior. Simulações computacionais são realizadas para evidenciar o desempenho das propostas frente a tecnicas conhecidas da literatura em varias situações de necessidade de alguma estrategia de recuperação de sinais / Abstract: This thesis is devoted to study blind source separation techniques applied to multiuser processing in digital communications. Using probability density function (pdf) estimation strategies, two multiuser processing methods are proposed. They aim for recovering transmitted signal by using the Kullback-Leibler similarity measure between the signals pdf and a parametric model that contains the signals characteristics. Besides the similarity measure, different methods are employed to guarantee the decorrelation of the sources estimates, providing that the recovered signals origin from different sources. The convergence analysis of the methods as well as their equivalences with classical techniques are presented, resulting on important relationships between blind and supervised criteria such as the proposal and the maximum a posteriori one. Those new methods have a good trade-off between the recovering ability and computational complexity. The proposal os pdf estimation-based methods had allowed the investigation on the impact of higher order statistics on adaptive algorithms for blind source separation. Using pdf orthonormal series expansion we are able to evaluate through cumulants the dynamics of a source separation process. To be able to deal with digital communication signals, a new orthonormal series expansion is proposed. Such expansion is developed in terms of a Gaussian mixture pdf. This new expansion is used to evaluate the differences in real time processing when we retain more higher order statistics. Computational simulations are carried out to stress the performance of the proposals, faced to well known techniques reported in the literature, under the situations where a recovering signal strategy is required. / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica