Space-time diversity for CDMA systems over frequency-selective fading channels

Supporting the expected high data rates required by wireless Internet and high-speed multimedia services is one of the basic requirements in broadband mobile wireless systems. However, the achievable capacity and data rate of wireless communication systems are limited by the time-varying nature of the channel. Efficient techniques for combating the time-varying effects of wireless channels can be achieved by utilizing different forms of diversity. In recent years, transmit diversity based on space-time coding (STC) has received more attention as an effective technique for combating fading. On the other hand, most existing space-time diversity techniques have been developed for flat-fading channels. Given the fact that wireless channels are generally frequency-selective, in this thesis, we aim to investigate the performance of space-time diversity schemes for wideband code-division multiple-access (WCDMA) systems over frequency-selective fading channels. The proposed receiver in this case is a rake-type receiver, which exploits the path diversity inherent to multipath propagation. Then, a decorrelator detector is used to mitigate the multiple access interference (MAI) and the known near-far problem. We derive the bit error rate (BER) expression over frequency-selective fading channels considering both the fast and slow fading cases. Finally, we show that our proposed receiver achieves the full system diversity through simulation and analytical results. Most of the work conducted in this area considers perfect knowledge of the channel at the receiver. Hence, channel identification brings significant challenges to multiple-input multiple-output (MIMO) CDMA systems. In light of this, we propose a channel estimation and data detection scheme based on the superimposed training-based approach. The proposed scheme enhances the performance by eliminating the MAI from both the channel and data estimates by employing two decorrelators; channel and data decorrelators. The performance of the proposed estimation technique is investigated over frequency-selective slow fading channels where we derived a closed-form expression for the BER as a function of the number of users, K , the number resolvable paths, L , and the number of receive antennas, V . Finally, our proposed scheme is shown to be more robust to channel estimation errors. Furthermore, both the analytical and simulation results indicate that the full system diversity is achieved. Considering that training estimation techniques suffer either from low spectral efficiency (i.e., conventional training approach) or from high pilot power consumption (i.e., superimposed training-based approach), in the last part of the thesis, we present an iterative joint detection and estimation (JDE) using the expectation-maximization (EM) algorithm for MIMO CDMA systems over frequency-selective fading channels. We also derive a closed-form expression for the optimized weight coefficients of the EM algorithm, which was shown to provide significant performance enhancement relative to the conventional equal-weight EM-based signal decomposition. Finally, our simulation results illustrate that the proposed receiver achieves near-optimum performance with modest complexity using very few training symbols

Blind source separation for interference cancellation in CDMA systems

Communication is the science of "reliable" transfer of information between two parties, in the sense that the information reaches the intended party with as few errors as possible. Modern wireless systems have many interfering sources that hinder reliable communication. The performance of receivers severely deteriorates in the presence of unknown or unaccounted interference. The goal of a receiver is then to combat these sources of interference in a robust manner while trying to optimize the trade-off between gain and computational complexity. Conventional methods mitigate these sources of interference by taking into account all available information and at times seeking additional information e.g., channel characteristics, direction of arrival, etc. This usually costs bandwidth. This thesis examines the issue of developing mitigating algorithms that utilize as little as possible or no prior information about the nature of the interference. These methods are either semi-blind, in the former case, or blind in the latter case. Blind source separation (BSS) involves solving a source separation problem with very little prior information. A popular framework for solving the BSS problem is independent component analysis (ICA). This thesis combines techniques of ICA with conventional signal detection to cancel out unaccounted sources of interference. Combining an ICA element to standard techniques enables a robust and computationally efficient structure. This thesis proposes switching techniques based on BSS/ICA effectively to combat interference. Additionally, a structure based on a generalized framework termed as denoising source separation (DSS) is presented. In cases where more information is known about the nature of interference, it is natural to incorporate this knowledge in the separation process, so finally this thesis looks at the issue of using some prior knowledge in these techniques. In the simple case, the advantage of using priors should at least lead to faster algorithms.reviewe

Transmitter based techniques for ISI and MAI mitigation in CDMA-TDD downlink

The third-generation (3G) of mobile communications systems aim to provide enhanced voice, text and data services to the user. These demands give rise to the complexity and power consumption of the user equipment (UE) while the objective is smaller, lighter and power efficient mobiles. This thesis aims to examine ways of reducing the UE receiver’s computational cost while maintaining a good performance. One prominent multiple access scheme selected for 3G is code division multiple access. Receiver based multiuser detection techniques that utilise the knowledge of the downlink channel by the mobile have been extensively studied in the literature, in order to deal with multiple access and intersymbol interference. However, these techniques result in high mobile receiver complexity. Recently, work has been done on algorithms that transfer the complexity from the UE to the base station by exploiting the fact that in time division duplex mode the downlink channel can be known to the transmitter. By linear precoding of the transmitted signal the user equipment can be simplified to a filter matched to the user’s spreading code. In this thesis the problem of generic linear precoding is analysed theoretically and a method for analytical calculation of BER is developed. The most representative of the developed precoding techniques are described under a common framework, compared and classified as bitwise or blockwise. Bitwise demonstrate particular advantages in terms of complexity and implementation but lack in performance. Two novel bitwise algorithms are presented and analysed. They outperform significantly the existing ones, while maintain a reduced computational cost and realisation simplicity. The first, named inverse filters, is the Wiener solution of the problem after applying a minimum mean squared error criterion with power constraints. The second recruits multichannel adaptive algorithms to achieve the same goal. The base station emulates the actual system in a cell to converge iteratively to the pre-filters that precode the transmitted signals before transmission. The advantages and the performance of the proposed techniques, along with a variety of characteristics are demonstrated by means of Monte Carlo simulations

Development of Novel Independent Component Analysis Techniques and their Applications

Real world problems very often provide minimum information regarding their causes. This is mainly due to the system complexities and noninvasive techniques employed by scientists and engineers to study such systems. Signal and image processing techniques used for analyzing such systems essentially tend to be blind. Earlier, training signal based techniques were used extensively for such analyses. But many times either these training signals are not practicable to be availed by the analyzer or become burden on the system itself. Hence blind signal/image processing techniques are becoming predominant in modern real time systems. In fact, blind signal processing has become a very important topic of research and development in many areas, especially biomedical engineering, medical imaging, speech enhancement, remote sensing, communication systems, exploration seismology, geophysics, econometrics, data mining, sensor networks etc. Blind Signal Processing has three major areas: Blind Signal Separation and Extraction, Independent Component Analysis (ICA) and Multichannel Blind Deconvolution and Equalization. ICA technique has also been typically applied to the other two areas mentioned above. Hence ICA research with its wide range of applications is quite interesting and has been taken up as the central domain of the present work

Proceedings of the Third International Mobile Satellite Conference (IMSC 1993)

Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial cellular communications services. While the first and second International Mobile Satellite Conferences (IMSC) mostly concentrated on technical advances, this Third IMSC also focuses on the increasing worldwide commercial activities in Mobile Satellite Services. Because of the large service areas provided by such systems, it is important to consider political and regulatory issues in addition to technical and user requirements issues. Topics covered include: the direct broadcast of audio programming from satellites; spacecraft technology; regulatory and policy considerations; advanced system concepts and analysis; propagation; and user requirements and applications

Nonlinear iterative multiuser detection and equalization for CDMA receivers in the presence of interchip interference

This paper addresses the problem of (nonlinear) iterative multiuser detection (MUD) for synchronous CDMA. In the literature, there are several related methods for solving this problem. These methods involve a linear estimator combined with nonlinear detection of the transmitted symbols but generally do not apply per-symbol iteration. However, the convergence analysis of iterative schemes has not been addressed yet (to our knowledge). In this paper, we present a new algorithm for MUD and provide a convergence analysis for an approximation to it. We believe this approach yields an understanding not only of the behavior of our proposed scheme but also of other possible iterative algorithms for MUD.Sylvie L. Perreau and Langford B. Whitehttp://www.elsevier.com/wps/find/journaldescription.cws_home/622818/description#descriptio