Smart antenna, which weights are obtained by Wiener solution, would suppress some undesired interference signals in spatial domain. The other interference signals that cannot be suppressed by smart antenna or caused by near-far effect will be post-processed by multiuser detectors. In the proposed algorithm, the cross-correlation matrix of desired signal and received signal from smart antenna algorithm would be applied to multiuser detector to reduce the complexity. From computer simulation results, the proposed algorithm has lower complexity and better BER performance than separate smart antenna or multiuser detection algorithms. Detail derivations of complexity and BER performance are also provided in this thesis.

Over the last decade, access to personal wireless communication networks has evolved to a point of necessity. Attached to the phenomenal growth of the telecommunications industry in recent times is an escalating demand for higher data rates and efficient spectrum utilization. This demand is fuelling the advancement of third generation (3G), as well as future, wireless networks. Current 3G technologies are adding a dimension of mobility to services that have become an integral part of modem everyday life. Wideband code division multiple access (WCDMA) is the standardized multiple access scheme for 3G Universal Mobile Telecommunication System (UMTS). As an air interface solution, CDMA has received considerable interest over the past two decades and a great deal of current research is concerned with improving the application of CDMA in 3G systems. A factoring component of CDMA is multiuser detection (MUD), which is aimed at enhancing system capacity and performance, by optimally demodulating multiple interfering signals that overlap in time and frequency. This is a major research problem in multipoint-to-point communications. Due to the complexity associated with optimal maximum likelihood detection, many different sub-optimal solutions have been proposed. This focus of this dissertation is the application of neural networks for MUD, in a direct sequence CDMA (DS-CDMA) system. Specifically, it explores how the Hopfield recurrent neural network (RNN) can be employed to give yet another suboptimal solution to the optimization problem of MUD. There is great scope for neural networks in fields encompassing communications. This is primarily attributed to their non-linearity, adaptivity and key function as data classifiers. In the context of optimum multiuser detection, neural networks have been successfully employed to solve similar combinatorial optimization problems. The concepts of CDMA and MUD are discussed. The use of a vector-valued transmission model for DS-CDMA is illustrated, and common linear sub-optimal MUD schemes, as well as the maximum likelihood criterion, are reviewed. The performance of these sub-optimal MUD schemes is demonstrated. The Hopfield neural network (HNN) for combinatorial optimization is discussed. Basic concepts and techniques related to the field of statistical mechanics are introduced and it is shown how they may be employed to analyze neural classification. Stochastic techniques are considered in the context of improving the performance of the HNN. A neural-based receiver, which employs a stochastic HNN and a simulated annealing technique, is proposed. Its performance is analyzed in a communication channel that is affected by additive white Gaussian noise (AWGN) by way of simulation. The performance of the proposed scheme is compared to that of the single-user matched filter, linear decorrelating and minimum mean-square error detectors, as well as the classical HNN and the stochastic Hopfield network (SHN) detectors. Concluding, the feasibility of neural networks (in this case the HNN) for MUD in a DS-CDMA system is explored by quantifying the relative performance of the proposed model using simulation results and in view of implementation issues. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2006.

No description available.

Turbo codes are a class of forward error correction (FEC) codes that offer energy efficiencies close to the limits predicted by information theory. The features of turbo codes include parallel code concatenation, recursive convolutional encoding, nonuniform interleaving, and an associated iterative decoding algorithm. Although the iterative decoding algorithm has been primarily used for the decoding of turbo codes, it represents a solution to a more general class of estimation problems that can be described as follows: a data set directly or indirectly drives the state transitions of two or more Markov processes; the output of one or more of the Markov processes is observed through noise; based on the observations, the original data set is estimated. This dissertation specifically describes the process of encoding and decoding turbo codes. In addition, a more general discussion of iterative decoding is presented. Then, several new applications of iterative decoding are proposed and investigated through computer simulation. The new applications solve two categories of problems: the detection of turbo codes over time-varying channels, and the distributed detection of coded multiple-access signals. Because turbo codes operate at low signal-to-noise ratios, the process of phase estimation and tracking becomes difficult to perform. Additionally, the turbo decoding algorithm requires precise estimates of the channel gain and noise variance. The first significant contribution of this dissertation is a study of several methods of channel estimation suitable specifically for turbo coded systems. The second significant contribution of this dissertation is a proposed method for jointly detecting coded multiple-access signals using observations from several locations, such as spatially separated base stations. The proposed system architecture draws from the concepts of macrodiversity combining, multiuser detection, and iterative decoding. Simulation results show that when the system is applied to the time division multiple-access cellular uplink, a significant improvement in system capacity results. / Ph. D.

The monitoring of traffic signal systems can be of great importance for identifying problems, self-assessment, budgeting, creating the strategy for future steps, etc. Monitoring procedure was developed through a set of dashboards with relevant signal performance and reliability measures. The dashboards were created to reflect performance and reliability of a specific signal system on a weekly or monthly level. The author used data from ATMS.now signal system central software to illustrate how similar dashboards could be developed from any central software to enable operators to promptly and efficiently monitor various parameters of traffic signals. The main outcome of the study is a pair of Excel dashboards accompanied with appropriate user manual. The dashboards represent the tool for monitoring which can be helpful in the process of evaluation for traffic signal systems. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Design and analysis of random-like codes for various multiple-input and multiple-output communication systems are addressed in this work. Random-like codes have drawn significant interest because they offer capacity-achieving performance. We first consider the analysis and design of low-density parity-check (LDPC) codes for turbo multiuser detection in multipath CDMA channels. We develop techniques for computing the probability density function (pdf) of the extrinsic messages at the output of the soft-input soft-output (SISO) multiuser detectors as a function of the pdf of input extrinsic messages, user spreading codes, channel impulse responses, and signal-to-noise ratios. Using these techniques, we are able to accurately compute the thresholds for LDPC codes and design good irregular LDPC codes. We then apply the tools of density evolution with mixture Gaussian approximations to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system configurations which include different number of antennas, different channel models and different demodulation schemes. We also study the coding-spreading tradeoff in LDPC coded CDMA systems employing multiuser joint decoding. We solve the coding-spreading optimization based on the extrinsic information SNR evolution curves for the SISO multiuser detectors and the SISO LDPC decoders. Both single-cell and multi-cell scenarios will be considered. For each of these cases, we will characterize the extrinsic information for both finite-size systems and the so-called large systems where asymptotic performance results must be evoked. Finally, we consider the design optimization of irregular repeat accumulate (IRA) codes for MIMO communication systems employing iterative receivers. We present the density evolution-based procedure with Gaussian approximation for optimizing the IRA code ensemble. We adopt an approximation method based on linear programming to design an IRA code with the extrinsic information transfer (EXIT) chart matched to that of the soft MIMO demodulator.

In general, ultra wideband (UWB) signals are transmitted using ~'eIYshort pulses m tiIae domain, thus promising very high data rates. In this thesis, a recei'ler structure is proposed for decoding multiuser information data in a convolutionally coded UWB system. The proposed iterative receiver has three stages: a pulse detector, a symbol detector, and a channel decoder. Each of these stages outputs soft values, which are used as a priori information in the next iteration. Simulation results show that the proposed system can provide performance very close to a single-user system. / Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering. / "July 2006." / Incluldes bibliographic references (leaves 29-31)

Recently, the transmission of vector quantization (VQ) over a code-division multiple access (CDMA) channel has received a considerable attention in research community. The complexity of the optimal decoding for VQ in CDMA communications is prohibitive for implementation, especially for systems with a medium or large number of users. A suboptimal approach to VQ decoding over a CDMA channel, disturbed by additive white Gaussian noise (AWGN), was recently developed. Such a suboptimal decoder is built from a soft-output multiuser detector (MUD), a soft bit estimator and the optimal soft VQ decoders of individual users. <p>Due to its lower complexity and good performance, such a decoding scheme is an attractive alternative to the complicated optimal decoder. It is necessary to extend this decoding scheme for a frequency-selective Rayleigh fading CDMA channel, a channel model typically seen in mobile wireless communications. This is precisely the objective of this thesis. <p>Furthermore, the suboptimal decoders are obtained not only for binary phase shift keying (BPSK), but also for M-ary pulse amplitude modulation (M-PAM). This extension offers a flexible trade-off between spectrum efficiency and performance of the systems. In addition, two algorithms based on distance measure and reliability processing are introduced as other alternatives to the suboptimal decoder. <p>Simulation results indicate that the suboptimal decoders studied in this thesis also performs very well over a frequency-selective Rayleigh fading CDMA channel.

Recently, the transmission of vector quantization (VQ) over a code-division multiple access (CDMA) channel has received a considerable attention in research community. The complexity of the optimal decoding for VQ in CDMA communications is prohibitive for implementation, especially for systems with a medium or large number of users. A suboptimal approach to VQ decoding over a CDMA channel, disturbed by additive white Gaussian noise (AWGN), was recently developed. Such a suboptimal decoder is built from a soft-output multiuser detector (MUD), a soft bit estimator and the optimal soft VQ decoders of individual users. <p>Due to its lower complexity and good performance, such a decoding scheme is an attractive alternative to the complicated optimal decoder. It is necessary to extend this decoding scheme for a frequency-selective Rayleigh fading CDMA channel, a channel model typically seen in mobile wireless communications. This is precisely the objective of this thesis. <p>Furthermore, the suboptimal decoders are obtained not only for binary phase shift keying (BPSK), but also for M-ary pulse amplitude modulation (M-PAM). This extension offers a flexible trade-off between spectrum efficiency and performance of the systems. In addition, two algorithms based on distance measure and reliability processing are introduced as other alternatives to the suboptimal decoder. <p>Simulation results indicate that the suboptimal decoders studied in this thesis also performs very well over a frequency-selective Rayleigh fading CDMA channel.

Design and analysis of random-like codes for various multiple-input and multiple-output communication systems are addressed in this work. Random-like codes have drawn signi&#64257;cant interest because they o&#64256;er capacity-achieving performance. We &#64257;rst consider the analysis and design of low-density parity-check (LDPC) codes for turbo multiuser detection in multipath CDMA channels. We develop techniques for computing the probability density function (pdf) of the extrinsic messages at the output of the soft-input soft-output (SISO) multiuser detectors as a function of the pdf of input extrinsic messages, user spreading codes, channel impulse responses, and signal-to-noise ratios. Using these techniques, we are able to accurately compute the thresholds for LDPC codes and design good irregular LDPC codes. We then apply the tools of density evolution with mixture Gaussian approximations to optimize irregular LDPC codes and to compute minimum operational signal-to-noise ratios for ergodic MIMO OFDM channels. In particular, the optimization is done for various MIMO OFDM system con&#64257;gurations which include di&#64256;erent number of antennas, di&#64256;erent channel models and di&#64256;erent demodulation schemes. We also study the coding-spreading tradeo&#64256; in LDPC coded CDMA systems employing multiuser joint decoding. We solve the coding-spreading optimization based on the extrinsic information SNR evolution curves for the SISO multiuser detectors and the SISO LDPC decoders. Both single-cell and multi-cell scenarios will be considered. For each of these cases, we will characterize the extrinsic information for both &#64257;nite-size systems and the so-called large systems where asymptotic performance results must be evoked. Finally, we consider the design optimization of irregular repeat accumulate (IRA) codes for MIMO communication systems employing iterative receivers. We present the density evolution-based procedure with Gaussian approximation for optimizing the IRA code ensemble. We adopt an approximation method based on linear programming to design an IRA code with the extrinsic information transfer (EXIT) chart matched to that of the soft MIMO demodulator.