Multiuser detection employing recurrent neural networks for DS-CDMA systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2006.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

Performance Evaluation of Phase Optimized Spreading Codes in Non Linear DS-CDMA Receiver

Spread spectrum (SS) is a modulation technique in which the signal occupies a bandwidth much larger than the minimum necessary to send the information. A synchronized reception with the code at the receiver is used for despreading the information before data recovery. Bandspread is accomplished by means of a code which is independent of the data. Bandspreading code is pseudo-random, thus the spread signal resembles noise. The coded modulation characteristic of SS system uniquely qualifies it for navigation applications. Any signal used in ranging is subject to time/distance relations. A SS signal has advantage that its phase is easily resolvable. Direct-sequence (DS) form of modulation is mostly preferred over Frequency Hopping system (FH) as FH systems do not normally possess high resolution properties. Higher the chip rate, the better the measurement capability. The basic resolution is one code chip. Initially, some existing code families e.g. Gold, Kasami (large and smal..

Nonlinear receivers for DS-CDMA

The growing demand for capacity in wireless communications is the driving force behind improving established networks and the deployment of a new worldwide mobile standard. Capacity calculations show that the direct sequence code division multiple access (DS-CDMA) technique has more capacity than the time division multiple access technique. Therefore, most 3rd generation mobile systems will incorporate some sort of DS-CDMA. In this thesis DS-CDMA receiver structures are investigated from the view point of pattern recognition which leads to new DS-CDMA receiver structures. It is known that the optimum DS-CDMA receiver has a nonlinear structure with prohibitive complexity for practical implementation. It is also known that the currently implemented receiver in 2nd generation DSCDMA mobile handsets has poor performance, because it suffers from multiuser interference. Consequently, this work focuses on sub-optimum nonlinear receivers for DS-CDMA in the downlink scenario. First, the thesis reviews DS-CDMA, established equalisers, DS-CDMA receivers and pattern recognition techniques. Then the new receivers are proposed. It is shown that DS-CDMA can be considered as a pattern recognition problem and hence, pattern recognition techniques can be exploited in order to develop DS-CDMA receivers. Another approach is to apply known equaliser structures for DS-CDMA. One proposed receiver is based on the Volterra series expansion and processes the received signal at the chip rate. Another receiver is a symbol rate radial basis function network (RBFN) receiver with reduced complexity. Subsequently, a receiver is proposed based on linear programming (LP) which is especially tailored for nonlinearly separable scenarios. The LP based receiver performance is equivalent to the known decorrelating detector in linearly separable scenarios. Finally, a hybrid receiver is proposed which combines LP and RBFN and which exploits knowledge gained from pattern recognition. This structure has lower complexity than the full RBF and good performance, and has a large potential for further improvements. Monte-Carlo simulations compare the proposed DS-CDMA receivers against established linear and nonlinear receivers. It is shown that all proposed receivers outperform the known linear receivers. The Volterra receiver’s complexity is relatively high for the performance gain achieved and might not suit practical implementation. The other receiver’s complexity was greatly reduced but it performs nearly as well as an optimum symbol by symbol detector. This thesis shows that DS-CDMA is a pattern recognition problem and that pattern recognition techniques can simplify DS-CDMA receiver structures. Knowledge is gained from the DSCDMA signal patterns which help to understand the problem of a DS-CDMA receiver. It should be noted that from the large number of known techniques, only a few pattern recognition techniques are considered in this work, and any further work should look at other techniques. Pattern recognition techniques can reduce the complexity of existing DS-CDMA receivers while maintaining performance, leading to novel receiver structures

Non-Linear Fuzzy Receivers for DS-CDMA Communication System

Direct sequence-code division multiple access (DS-CDMA) technique is used in cellular systems where users in the cell are separated from each other with their unique spreading codes. In recent times DS-CDMA has been used extensively. These systems suffers from multiple access interference (MAI) due to other users transmitting in the cell, channel inter symbol interference (ISI) due to multipath nature of channels in presence of additive white Gaussian noise (AWGN). This thesis presents an investigation on design of fuzzy based receivers for DS-CDMA system. Fuzzy based receiver has been proposed to work as chip level based (CLB) receivers and also multi user detection (MUD) receivers. It is seen that fuzzy receiver is capable of providing performance close to optimal radial basis function (RBF) receivers and provide considerable computational complexity reduction. Extensive simulation studies demonstrate the performance of the fuzzy receivers and the performance have been compared with RAKE receiver, matched filter (MF) receiver, minimum mean square error (MMSE) receiver and RBF receiver

New Detection Methods for Transmission at Faster-Than-Nyquist Rates Using Quasi-Orthogonal Sequences

Direct sequence spread spectrum (DSSS) was initially used for anti-jamming in military applications and was later developed in other commercial applications. Walsh codes, which are a set of mutually orthogonal codes, are one type of the spreading codes used in DSSS systems. For any spreading codes of length N, these exist exactly N mutually orthogonal spreading codes; applying more than N codes to transmit data simultaneously will introduce interference among the transmitted data. For interference-free detection, the symbol rate is thus bounded by the Nyquist transmission rate with DSSS codes, assuming the traditional correlation receivers. The goal of this thesis is to explore new detection methods for signaling with faster-than-Nyquist transmission rates. First, new sets of quasi-orthogonal codes are designed to allow simultaneous transmission of data with more than N codes of length N each. Thus there exists mutual interference among the transmitted data. Then, a multi-layer perceptron (MLP) detection scheme with three layers is proposed for detecting the signal transmitted at faster-than-Nyquist rates using the quasi-orthogonal sequences. Finally, a long-short-term-memory (LSTM) scheme is proposed for detection in the proposed signaling scheme. The performances of these schemes are analyzed and simulated, and compared with the traditional correlation detection schemes

Design and Analysis of OFDM System for Powerline Based Communication

Research on digital communication systems has been greatly developed in the past few years and offers a high quality of transmission in both wired and wireless communication environments. Coupled with advances in new modulation techniques, Orthogonal Frequency Division Multiplexing (OFDM) is a well-known digital multicarrier communication technique and one of the best methods of digital data transmission over a limited bandwidth. The main aim of this research is to design an OFDM modem for powerline-based communication in order to propose and examine a novel approach in comparing the different modulation order, different modulation type, application of Forward Error Correction (FEC) scheme and also application of different noise types and applying them to the two modelled channels, Additive White Gaussian Noise (AWGN) and Powerline modelled channel. This is an attempt to understand and recognise the most suitable technique for the transmission of message or image within a communication system. In doing so, MATLAB and embedded Digital Signal Processing (DSP) systems are used to simulate the operation of virtual transmitter and receiver. The simulation results presented in this project suggest that lower order modulation formats (Binary Phase Shift Keying (BPSK) and 4-Quadrature Amplitude Modulation (QAM)), are the most preferred modulation techniques (in both type and order) for their considerable performance. The results also indicated that, Convolutional Channel Encoding (CCE)-Soft and Block Channel Encoding (BCE)-Soft are by far the best encoding techniques (in FEC type) for their best performance in error detection and correction. Indeed, applying these techniques to the two modelled channels has proven very successful and will be accounted as a novel approach for the transmission of message or image within a powerline based communication system

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin