Modem design for digital satellite communications

The thesis is concerned with the design of a phase-shift keying system for a digital modem, operating over a satellite link. Computer simulation tests and theoretical analyses are used to assess the proposed design. The optimum design of both transmitter and receiver filters for the system to be used in the modem are discussed. Sinusoidal roll-off spectrum with different roll-off factor and optimum truncation lengths of the sample impulse response are designed for the proposed scheme to approximate to the theoretical ideal. It has used an EF bandpass filter to band limit the modulated signal, which forms part of the satellite channel modelling. The high power amplifier (HPA) at the earth station has been used in the satellite channel modelling due to its effect in introducing nonlinear AMAM and AM-PM conversion effects and distortion on the transmitted signal from the earth station. The satellite transponder is assumed to be operating in a linear mode. Different phase-shift keying signals such as differentially encoded quaternary phase-shift keying (DEQPSK), offset quaternary phase-shift keying (OQPSK) and convolutionally encoded 8PSK (CE8PSK) signals are analysed and discussed in the thesis, when the high power amplifier (HPA) at the earth station is operating in a nonlinear mode. Convolutional encoding is discussed when applied to the system used in the modem, and a Viterbi -algorithm decoder at the receiver has been used, for CE8PSK signals for a nonlinear satellite channel. A method of feed-forward synchronisation scheme is designed for carrier recovery in CE8PSK receiver. The thesis describes a method of baseband linearizing the baseband signal in order to reduce the nonlinear effects caused by the HPA at the earth station. The scheme which compensates for the nonlinear effects of the HPA by predistorting the baseband signal prior to modulation as opposed to correcting the distortion after modulation, thus reducing the effects of nonlinear distortion introduced by the HPA. The results of the improvement are presented. The advanced technology of digital signal processors (DSPs) has been used in the implementation of the demodulation and digital filtering parts of the modem replacing large parts of conventional circuits. The Viterbi-algorithm decoder for CE8PSK signals has been implemented using a digital signal processor chip, giving excellent performance and is a cost effective and easy way for future developments and any modifications, The results showed that, by using the various studied techniques, as well as the implementation of digital signal processor chip in parts of the modem, a potentially more cost effective modem can be obtained

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and sectionalization of trellises. Chapter 7 discusses trellis decomposition and subtrellises for low-weight codewords. Chapter 8 first presents well known methods for constructing long powerful codes from short component codes or component codes of smaller dimensions, and then provides methods for constructing their trellises which include Shannon and Cartesian product techniques. Chapter 9 deals with convolutional codes, puncturing, zero-tail termination and tail-biting.Chapters 10 through 13 present various trellis-based decoding algorithms, old and new. Chapter 10 first discusses the application of the well known Viterbi decoding algorithm to linear block codes, optimum sectionalization of a code trellis to minimize computation complexity, and design issues for IC (integrated circuit) implementation of a Viterbi decoder. Then it presents a new decoding algorithm for convolutional codes, named Differential Trellis Decoding (DTD) algorithm. Chapter 12 presents a suboptimum reliability-based iterative decoding algorithm with a low-weight trellis search for the most likely codeword. This decoding algorithm provides a good trade-off between error performance and decoding complexity. All the decoding algorithms presented in Chapters 10 through 12 are devised to minimize word error probability. Chapter 13 presents decoding algorithms that minimize bit error probability and provide the corresponding soft (reliability) information at the output of the decoder. Decoding algorithms presented are the MAP (maximum a posteriori probability) decoding algorithm and the Soft-Output Viterbi Algorithm (SOVA) algorithm. Finally, the minimization of bit error probability in trellis-based MLD is discussed

Frame synchronization for PSAM in AWGN and Rayleigh fading channels

Pilot Symbol Assisted Modulation (PSAM) is a good method to compensate for the channel fading effect in wireless mobile communications. In PSAM, known pilot symbols are periodically inserted into the transmitted data symbol stream and the receiver uses these symbols to derive amplitude and phase reference. One aspect of this procedure, which has not received much attention yet, is the frame synchronization, i.e. the method used by the receiver to locate the time position of the pilot symbols. In this study, two novel non-coherent frame synchronization methods are introduced in which only the magnitude of received signal is used to obtain the timing of the pilot symbol. The methods are evaluated for both AWGN and frequency non-selective slow Rayleigh fading channels. One synchronization technique is derived by standard maximum likelihood (ML) estimation formulation, and the other is obtained by using maximum a Posteriori probability (MAP) with a threshold test. Signal processing in the receiver uses simplifying approximations that rely on relatively high signal-to-noise ratio (SNR) as consistent with the reception of 16-QAM. Computer simulation has been used to test the acquisition time performance and the probability of false acquisition. Several lengths and patterns of pilot symbol sequences were tested where every 10th symbol was a pilot symbol and all other symbols were randomly selected data symbols. When compared with the other published synchronizers, results from this study show better performance in both AWGN and fading channels. Significantly better performance is observed in the presence of receiver frequency offsets

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

Hidden Markov Models

Hidden Markov Models (HMMs), although known for decades, have made a big career nowadays and are still in state of development. This book presents theoretical issues and a variety of HMMs applications in speech recognition and synthesis, medicine, neurosciences, computational biology, bioinformatics, seismology, environment protection and engineering. I hope that the reader will find this book useful and helpful for their own research