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.

The Orthogonal frequency division multiplexing (OFDM) technique has been intensively used in many wireless communication systems to achieve higher data rate transmissions. Due to the fact that the OFDM technique entails redundant block transmissions; the transmitted blocks suffer from the inter-symbol interference (ISI) and inter-block interference (IBI). To compensate this serious effect, in many literatures redundant symbols (or guard interval) with adequate length are inserted in the transmitted symbols to prevent the IBI. Also, in the receiver the equalizer can be employed to deal with ISI. In this thesis, we present a new pseudo random cyclic-postfix (PRCP-) OFDM associated with the multiple-input multiple-output (MIMO) antenna system configuration to further improve the system performance. In fact, the MIMO system can enhance channel capacity and achieve high data-rate. The above-mentioned PRCP-OFDM technique combines with the MIMO antennas system, through the appropriate model design can be used to combat the multi-path effect or the inter-block interference. As evident from the simulation results, the proposed ST-BC MIMO PRCP-OFDM system can avoid the interference of transmitted signals during the estimation of channel impulse response (CIR) with proposed cyclic-postfix sequences. In addition, to further improve and eliminate the residual IBI and ICI, the equalizer with the framework of the generalized sidelobe canceller (GSC) is considered. Specifically, when SNR grows, the proposed ST-BC MIMO PRCP-OFDM system can perform successfully in terms of symbol-error rate and semi-blind channel estimation. This is verified via the computer simulations.

Capacity of CDMA system is limited to interference due to other users. System performance is degraded by near-far problem when undesired users are closer to base station. Beside, the channel parameters could not be estimated perfectly at receiver, refer to as mismatch problem, which would also degrade the system performance. We would like to consider the MAI and near-far interference cancellation by adaptive linear constraint algorithms to implement linear constraint minimum variance (LCMV) approach. To exploit the linearly constrained filtering, the structure of the generalized side-lobe canceller (GSC) has been employed, where the constrained problem is converted into an unconstrained form with fewer parameters. GSC structure is an indirect but simpler implementation of LCMV algorithm. Moreover, it is also known that the constant modulus (CM) criteria has advantage to combat the channel mismatch, and the performance of the adaptive constraint algorithm based on CM criteria will be investigate. In this thesis, we will derive a new GSC-IQRD-RLS algorithm to combat MAI and near-far problems by combining LC-IQRD-RLS algorithm [1][5] and GSC structure [17]; and prove that the GSC and LC structures based IQRD-RLS algorithms are equivalent, which means that the good performance of LC-IQRD-RLS algorithm can be achieved by a simpler GSC structure algorithm. We will also derive a new GSC-CM-IQRD-RLS algorithm to improve the system performance under mismatch problem by combining CM criteria [20] and GSC-IQRD-RLS algorithm.

The conventional temporal filtering approach cannot be used to separate signal from interference which occupies the same temporal frequency band as signal. Using a spatial filtering at the receiver can separate signals from interference that originates from different spatial location. Many adaptive array beamforming algorithms, based on linear constraints, have been proposed for suppressing undesired interference and being applied to wireless communication systems for multiuser detection. The adaptive array system can be employed to automatically adjust its directional to achieve the purpose that nulls the interferences or jammers and thus, enhances the reception of the desired signal. Inverse QR Decomposition Recursive Least-square (IQRD-RLS) algorithm has many advantages such as where the LS weight vector be computed without back substitution, a well known numerical stable algorithm and offering better convergence rate, steady-state means-square error, and parameter tracking capability over the adaptive least mean square (LMS) based algorithms. In this thesis, a new application, GSC-IQRD-RLS combining Generalized Sidelobe Canceller (GSC) and IQRD-RLS algorithm, is developed. It preserves the advantages of GSC such as simple structure, less computations, and converts a linearly constrained optimization problem into a standard optimum filtering problem. But the performance is equivalent between GSC-IQRD-RLS and LC-IQRD-RLS algorithms.

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.

The direct-sequence code division multiple access (DS-CDMA) is one of the significant techniques for wireless communication systems with multiple simultaneous transmissions. The main concern of this thesis is to propose a new linearly constrained constant modulus modified conjugate gradient (LCCM-MCG) adaptive filtering algorithm to deal with problem of channel mismatch associated with the multiple access interference (MAI) in DS-CDMA system over multipath fading channel. In fact, the adaptive filtering algorithm based on the CM criterion is known to be very attractive for the case when the channel parameters are not estimated perfectly. The proposed LCCM-MCG algorithm is derived based on the so-called generalized sidelobe canceller (GSC). It has the advantage of having better stability and less computational complexity compared with conventional recursive least-squares (RLS) algorithm, and can be used to achieve desired performance for multiuser RAKE receiver. Moreover, with the MCG algorithm it requires only one recursive iteration per incoming sample data for updating the weight vector, but still maintains performance comparable to the RLS algorithm. From computer simulation results, we show that the proposed LCCM-MCG algorithm has fast convergence rate and could be used to circumvent the effect due to channel mismatch. Also, the performance, in terms of bit error rate (BER), is quite close to the LCCM-RLS algorithm suggested in [18], and is superior to the stochastic gradient descent (SGD) algorithm proposed in [7].

In aeroacoustic experiments of aircraft models and/or components, arrays of microphones are utilized to spatially isolate distinct sources and mitigate interfering noise which contaminates single-microphone measurements. Array measurements are still biased by interfering noise which is coherent over the spatial array aperture. When interfering noise is accounted for, existing algorithms which aim to both spatially isolate distinct sources and determine their individual levels as measured by the array are complex and require assumptions about the nature of the sound field. This work develops a processing scheme which uses spatially-defined phase constraints to remove correlated, interfering noise at the single-channel level. This is achieved through a merger of Conditioned Spectral Analysis (CSA) and the Generalized Sidelobe Canceller (GSC). A cross-spectral, frequency-domain filter is created using the GSC methodology to edit the CSA formulation. The only constraint needed is the user-defined, relative phase difference between the channel being filtered and the reference channel used for filtering. This process, titled Constrained Spectral Conditioning (CSC), produces single-channel Fourier Transform estimates of signals which satisfy the user-defined phase differences. In a spatial sound field mapping context, CSC produces sub-datasets derived from the original which estimate the signal characteristics from distinct locations in space. Because single-channel Fourier Transforms are produced, CSC's outputs could theoretically be used as inputs to many existing algorithms. As an example, data-independent, frequency-domain beamforming (FDBF) using CSC's outputs is shown to exhibit finer spatial resolution and lower sidelobe levels than FDBF using the original, unmodified dataset. However, these improvements decrease with Signal-to-Noise Ratio (SNR), and CSC's quantitative accuracy is dependent upon accurate modeling of the sound propagation and inter-source coherence if multiple and/or distributed sources are measured. In order to demonstrate systematic spatial sound mapping using CSC, it is embedded into the CLEAN algorithm which is then titled CLEAN-CSC. Simulated data analysis indicates that CLEAN-CSC is biased towards the mapping and energy allocation of relatively stronger sources in the field, which limits its ability to identify and estimate the level of relatively weaker sources. It is also shown that CLEAN-CSC underestimates the true integrated levels of sources in the field and exhibits higher-than-true peak source levels, and these effects increase and decrease respectively with increasing frequency. Five independent scaling methods are proposed for correcting the CLEAN-CSC total integrated output levels, each with their own assumptions about the sound field being measured. As the entire output map is scaled, these do not account for relative source level errors that may exist. Results from two airfoil tests conducted in NASA Langley's Quiet Flow Facility show that CLEAN-CSC exhibits less map noise than CLEAN yet more segmented spatial sound distributions and lower integrated source levels. However, using the same source propagation model that CLEAN assumes, the scaled CLEAN-CSC integrated source levels are brought into closer agreement with those obtained with CLEAN. / Ph. D.