[Truncated abstract] The transmission of digital information over a wireless communication channel gives rise to a number of issues which can detract from the system performance. Propagation effects such as multipath fading and intersymbol interference (ISI) can result in significant performance degradation. Recent developments in the field of iterative detection have led to a number of powerful strategies that can be effective in mitigating the detrimental effects of wireless channels. In this thesis, iterative detection is considered for use in two distinct areas of wireless communications. The first considers the iterative decoding of concatenated block codes over slow flat fading wireless channels, while the second considers the problem of detection for a coded communications system transmitting over highly-dispersive frequency-selective wireless channels. The iterative decoding of concatenated codes over slow flat fading channels with coherent signalling requires knowledge of the fading amplitudes, known as the channel state information (CSI). The CSI is combined with statistical knowledge of the channel to form channel reliability metrics for use in the iterative decoding algorithm. When the CSI is unknown to the receiver, the existing literature suggests the use of simple approximations to the channel reliability metric. However, these works generally consider low rate concatenated codes with strong error correcting capabilities. In some situations, the error correcting capability of the channel code must be traded for other requirements, such as higher spectral efficiency, lower end-to-end latency and lower hardware cost. ... In particular, when the error correcting capabilities of the concatenated code is weak, the conventional metrics are observed to fail, whereas the proposed metrics are shown to perform well regardless of the error correcting capabilities of the code. The effects of ISI caused by a frequency-selective wireless channel environment can also be mitigated using iterative detection. When the channel can be viewed as a finite impulse response (FIR) filter, the state-of-the-art iterative receiver is the maximum a posteriori probability (MAP) based turbo equaliser. However, the complexity of this receiver's MAP equaliser increases exponentially with the length of the FIR channel. Consequently, this scheme is restricted for use in systems where the channel length is relatively short. In this thesis, the use of a channel shortening prefilter in conjunction with the MAP-based turbo equaliser is considered in order to allow its use with arbitrarily long channels. The prefilter shortens the effective channel, thereby reducing the number of equaliser states. A consequence of channel shortening is that residual ISI appears at the input to the turbo equaliser and the noise becomes coloured. In order to account for the ensuing performance loss, two simple enhancements to the scheme are proposed. The first is a feedback path which is used to cancel residual ISI, based on decisions from past iterations. The second is the use of a carefully selected value for the variance of the noise assumed by the MAP-based turbo equaliser. Simulations are performed over a number of highly dispersive channels and it is shown that the proposed enhancements result in considerable performance improvements. Moreover, these performance benefits are achieved with very little additional complexity with respect to the unmodified channel shortened turbo equaliser.

Digital technology has made complex signal processing possible in communication systems and greatly improved the performance and quality of most modern telecommunication systems. The telecommunication industry and specifically mobile wireless telephone and computer networks have shown phenomenal growth in both the number of subscribers and emerging services, resulting in rapid consumption of common resources of which the electromagnetic spectrum is the most important. Technological advances and research in digital communication are necessary to satisfy the growing demand, to fuel the demand and to exploit all the possibilities and business opportunities. Efficient management and distribution of resources facilitated by state-of-the-art algorithms are indispensable in modern communication networks. The challenge in communication system design is to construct a system that can accurately reproduce the transmitted source message at the receiver. The channel connecting the transmitter and receiver introduces detrimental effects and limits the reliability and speed of information transfer between the source and destination. Typical channel effects encountered in mobile wireless communication systems include path loss between the transmitter and receiver, noise caused by the environment and electronics in the system, and fading caused by multiple paths and movement in the communication channel. In multiple access systems, different users cause interference in each other’s signals and adversely affect the system performance. To ensure reliable communication, methods to overcome channel effects must be devised and implemented in the system. Techniques used to improve system performance and capacity include temporal, frequency, polarisation and spatial diversity. This dissertation is concerned mainly with temporal or time diversity. Channel coding is a temporal diversity scheme and aims to improve the system error performance by adding structured redundancy to the transmitted message. The receiver exploits the redundancy to infer with greater accuracy which message was transmitted, compared with uncoded systems. Sparse graph codes are channel codes represented as sparse probabilistic graphical models which originated in artificial intelligence theory. These channel codes are described as factor graph structures with bit nodes, representing the transmitted codeword bits, and bit-constrained or check nodes. Each constraint involves only a small number of code bits, resulting in a sparse factor graph with far fewer connections between bit and check nodes than the maximum number of possible connections. Sparse graph codes are iteratively decoded using message passing or belief propagation algorithms. Three classes of iteratively decodable channel codes are considered in this study, including low-density parity-check (LDPC), Turbo and repeat-accumulate (RA) codes. The modulation platform presented in this dissertation is a spectrally efficient wideband system employing orthogonal complex spreading sequences (CSSs) to spread information sequences over a wider frequency band in multiple modulation dimensions. Special features of these spreading sequences include their constant envelopes and power output, providing communication range or device battery life advantages. This study shows that multiple layer modulation (MLM) can be used to transmit parallel data streams with improved spectral efficiency compared with single-layer modulation, providing data throughput rates proportional to the number of modulation layers at performances equivalent to single-layer modulation. Alternatively, multiple modulation layers can be used to transmit coded information to achieve improved error performance at throughput rates equivalent to a single layer system / Dissertation (MEng (Electronic Engineering))--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / unrestricted