In this thesis, a novel pre-coded direct-sequence code division multiple access (DS-CDMA) associated with the multiple-input multiple-output (MIMO) antennas, along with Alamouti¡¦s space-time block code (ST-BC) is considered. In the transmitter, the idea of hybrid pre-coded is exploited; it can be employed to counteract the inter-symbol interference (ISI) introduced by the channel fading duo to multipath propagation, and can be used to exacting the full information of channel impulse response (CIR) in the receiver for semi-blind channel estimation. Under this transceiver framework, we develop a semi-blind adaptive MIMO-CDMA receiver, based on the linearly constrained constant modulus (LCCM) criterion, for symbol recovery. Furthermore, to reduce the complexity of receiver design, the framework of the generalized sidelobe canceller (GSC) associated with the recursive least-squares (RLS) algorithm is adopted, and the gradient approach is applied to track the desired user¡¦s amplitude, simultaneously, and is named as the GSC-CM-IQRD-RLS algorithm. Via computer simulations, the superior performance and the advantages of proposed scheme is verified; it outperforms the conventional LCMV-based algorithm, and slightly better than the convention CM-GSC-RLS receiver, with the paid of spectral efficient.

In this thesis, we present a new low-complexity receiver with the modified hybrid signature direct-sequence code division multiple access (DS-CDMA) system framework that use the multiple-input multiple-output (MIMO) antennas along with Alamouti¡¦s space-time block code (ST-BC). In the transceiver, the modified hybrid signature is exploited. It is not only used to counteract the inter-symbol interference (ISI) introduced by the channel fading duo to multipath propagation but also very useful for extracting the full channel information in the receiver. For reducing computational complexity, we propose a new modified partial adaptivity (MPA) filter. It is not only having the advantage of subspace-based PA-GSC filter to enhance the system performance but also avoid the computation requirement when the Eigen-decomposition approach was adopted. Next, with the modified transceiver framework, in the receiver, based on the linearly constrained constant modulus (LCCM) criterion, we propose a novel semi-blind multiple detector schemes for MIMO-CDMA systems, which is implementing with the adaptive RLS algorithm and framework in the modified partially adaptive (MPA) generalized sidelobe canceller (GSC) . Our proposed scheme is able to perform the two-branch filterbank of LCCM MIMO-CDMA receiver. Computer simulations demonstrate that the proposed receiver has better performance than the convention CM-GSC-RLS receiver with much lower computational load.

In recent years, demands on all kinds of wireless communications become heavier due to the developments of new services and devices. At the same time, future wireless networks are expected to provide services with high quality and data rate. A possible solution which can attain these objectives is wireless communication systems that use multiple-input multiple-output (MIMO) antennas along with Alamouti¡¦s space-time block code and direct-sequence code division multiple access (DS-CDMA) modulation technique. In such systems, spatial diversity rendered by multiple antennas as well as coding in spatial and time domains are the keys to improve quality of transmission. Many multiuser detection techniques for the space-time block coded CDMA systems have been investigated. In [8], the blind Capon receiver was proposed, which consists of a two-branch filterbank followed by the blind Capon channel estimator. The design of blind Capon receiver is based on linearly constrained minimum variance (LCMV) criterion, which is known to be sensitive to inaccuracies in the acquisition or tracking of the desired user's timing, referred to as mismatch effect. In other words, the LCMV-based receiver may perform undesirably under mismatch effect. In this thesis, we propose a new blind adaptive MIMO-CDMA receiver based on the linearly constrained constant modulus (LCCM) criterion. This work is motivated by the robustness of LCCM approach to the mismatch effect. To reduce the complexity of receiver design, framework of the generalized sidelobe canceller (GSC) associated with the recursive least squares (RLS) algorithm is adopted for implementing the adaptive LCCM MIMO-CDMA filterbank. Based on the GSC-RLS structure, we derive the proposed MIMO CM-GSC-RLS algorithm. For the purpose of comparison, an adaptive implementation of the blind Capon receiver proposed in [8] is also derived, which is referred to as the MIMO MV-GSC-RLS algorithm. We note that the signal model in [8] was constructed under assumption of frequency-flat channels. To obtain a more practical and realistic signal model, in this thesis we extend the system and channel model by including multipath effects in the beginning of our work. In completing this extension, inter-symbol interference (ISI) caused by the special coding scheme of ST-BC will be specifically analyzed. Finally, a full discussion of the multipath signal model will be provided, including necessity of truncating the received signals as well as modifications in the signal model when considering time-varying channels. Via computer simulations, advantages of the proposed scheme will be verified. Compared to the conventional blind Capon receiver, we will show that the performance of the proposed CM-GSC-RLS algorithm is better. This is especially true when mismatch problem is considered in the MIMO-CDMA systems of interest. The proposed scheme show more robustness against the mismatch effects than the conventional blind Capon receiver. Moreover, the benefit resulted by truncating the received signals is also demonstrated, especially for binary phase-shift-keying (BPSK) modulated source symbol. Finally, simulations considering time-varying channels are provided to reveal that our proposed scheme can adapt itself to the time-varying environments appropriately.

In this thesis, we present a new hybrid pre-coded direct-sequence code division multiple access (DS-CDMA) system framework that use the multiple-input multiple-output (MIMO) antennas along with Alamouti¡¦s space-time block code (ST-BC). In the transmitter, the idea of hybrid pre-coded is exploited. It not only used to counteract the inter-symbol interference (ISI) introduced by the channel fading duo to multipath propagation but also very useful for exacting the phase of channel by appropriate design, which is not adopted in the conventional blind receiver. Under this structure, we propose a new blind adaptive MIMO-CDMA receiver based on the linearly constrained constant modulus (LCCM) criterion. To reduce the complexity of receiver design, framework of the generalized sidelobe canceller (GSC) associated with the recursive least square (RLS) algorithm is adopted for implementing the LCCM MIMO-CDMA receiver, and use gradient method to track the desired user¡¦s amplitude, simultaneously. Via computer simulations, advantages of the proposed scheme will be verified. Compared to the conventional blind Capon receiver, we will show that the performance of the proposed scheme is more robust against inaccuracies in the acquisition of the desired user¡¦s timing.

Researchers have shown that by combining multiple input multiple output (MIMO) techniques with CDMA then higher gains in capacity, reliability and data transmission speed can be attained. But a major drawback of MIMO-CDMA systems is multiple access interference (MAI) which can reduce the capacity and increase the bit error rate (BER), so statistical analysis of MAI becomes a very important factor in the performance analysis of these systems. In this thesis, a detailed analysis of MAI is performed for binary phase-shift keying (BPSK) signals with random signature sequence in Raleigh fading environment and closed from expressions for the probability density function of MAI and MAI with noise are derived. Further, probability of error is derived for the maximum Likelihood receiver. These derivations are verified through simulations and are found to reinforce the theoretical results. Since the performance of MIMO suffers significantly from MAI and inter-symbol interference (ISI), equalization is needed to mitigate these effects. It is well known from the theory of constrained optimization that the learning speed of any adaptive filtering algorithm can be increased by adding a constraint to it, as in the case of the normalized least mean squared (NLMS) algorithm. Thus, in this work both linear and non-linear decision feedback (DFE) equalizers for MIMO systems with least mean square (LMS) based constrained stochastic gradient algorithm have been designed. More specifically, an LMS algorithm has been developed , which was equipped with the knowledge of number of users, spreading sequence (SS) length, additive noise variance as well as MAI with noise (new constraint) and is named MIMO-CDMA MAI with noise constrained (MNCLMS) algorithm. Convergence and tracking analysis of the proposed algorithm are carried out in the scenario of interference and noise limited systems, and simulation results are presented to compare the performance of MIMO-CDMA MNCLMS algorithm with other adaptive algorithms.

CoordenaÃÃo de AperfeiÃoamento de NÃvel Superior / Em diversas aplicaÃÃes do processamento de sinais em sistemas de comunicaÃÃo sem-fio, o sinal recebido à de natureza multidimensional, possuindo uma estrutura algÃbrica multilinear. Neste contexto, a decomposiÃÃo tensorial PARAFAC tem sido utilizada em vÃrios trabalhos ao longo dos Ãltimos seis anos. Observa-se, entretanto, que decomposiÃÃes tensoriais generalizadas sÃo necessÃrias para modelar uma classe mais ampla de sistemas de comunicaÃÃo, caracterizada pela presenÃa de estruturas de transmissÃo mais complexas, por modelos de canal mais realistas, e por tÃcnicas de processamento de sinais mais eficientes no receptor. Esta tese investiga novas abordagens tensorias e suas aplicaÃÃes em modelagem de sistemas MIMO, equalizaÃÃo, separaÃÃo de sinais e estimaÃÃo paramÃtrica de canal. Inicialmente, duas novas decomposiÃÃes tensoriais (PARAFAC em blocos com restriÃÃes e CONFAC) sÃo desenvolvidas e estudadas em termos de identificabilidade. Em uma segunda parte do trabalho, novas aplicaÃÃes destas decomposiÃÃes tensoriais sÃo propostas. A decomposiÃÃo PARAFAC em blocos com restriÃÃes à aplicada, primeiramente, Âa modelagem unificada de sistemassuperamostrados, DS-CDMA e OFDM, com aplicaÃÃo em equalizaÃÃo multiusuÃria. Em seguida, esta decomposiÃÃo à utilizada na modelagem de sistemas de transmissÃo MIMO com espalhamento espaÃo-temporal e detecÃÃo conjunta. Em seguida, a decomposiÃÃo CONFAC à explorada na concepÃÃo de uma nova arquitetura generalizada de transmissÃo MIMO/CDMA que combina diversidade e multiplexagem. As propriedades de unicidade desta decomposiÃÃo permitem o uso do processamento nÃo-supervisionado no receptor, visando a reconstruÃÃo dos sinais transmitidos e a estimaÃÃo do canal. Na terceira e Ãltima parte deste trabalho, explora-se a decomposiÃÃo PARAFAC no contexto de duas aplicaÃÃes diferentes. Na primeira, uma nova estrutura de transmissÃo espaÃo-temporal-freqÃencial à proposta para sistemas MIMO multiportadora. A segunda aplicaÃÃo consiste em um novo estimador paramÃtrico para canais multipercursos. / In several signal processing applications for wireless communications, the received signal is multidimensional in nature and may exhibit a multilinear algebraic structure. In this context, the PARAFAC tensor decomposition has been the subject of several works in the past six years. However, generalized tensor decompositions are necessary for covering a wider class of wireless communication systems with more complex transmission structures, more realistic channel models and more efficient receiver signal processing. This thesis investigates tensor modeling approaches for multiple-antenna systems, channel equalization, signal separation and parametric channel estimation. New tensor decompositions, namely, the block-constrained PARAFAC and CONFAC decompositions, are developed and studied in terms of identifiability. First, the block-constrained PARAFAC decomposition is applied for a uniÂed tensor modeling of oversampled, DS-CDMA and OFDM systems with application to blind multiuser equalization. This decomposition is also used for modeling multiple-antenna (MIMO) transmission systems with block space-time spreading and blind detection, which generalizes previous tensor-based MIMO transmission models. The CONFAC decomposition is then exploited for designing new MIMO-CDMA transmission schemes combining spatial diversity and multiplexing. Blind symbol/code/channel recovery is discussed from the uniqueness properties of this decomposition. This thesis also studies new applications of third-order PARAFAC decomposition. A new space-time-frequency spreading system is proposed for multicarrier multiple-access systems, where this decomposition is used as a joint spreading and multiplexing tool at the transmitter using tridimensional spreading code with trilinear structure. Finally, we present a PARAFAC modeling approach for the parametric estimation of SIMO and MIMO multipath wireless channels with time-varying structure.