A simple importance sampling technique for orthogonal space-time block codes on Nakagami fading channels

In this contribution, we present a simple importance sampling technique to considerably speed up Monte Carlo simulations for bit error rate estimation of orthogonal space-time block coded systems on spatially correlated Nakagami fading channels

Wireless Channel Equalization in Digital Communication Systems

Our modern society has transformed to an information-demanding system, seeking voice, video, and data in quantities that could not be imagined even a decade ago. The mobility of communicators has added more challenges. One of the new challenges is to conceive highly reliable and fast communication system unaffected by the problems caused in the multipath fading wireless channels. Our quest is to remove one of the obstacles in the way of achieving ultimately fast and reliable wireless digital communication, namely Inter-Symbol Interference (ISI), the intensity of which makes the channel noise inconsequential. The theoretical background for wireless channels modeling and adaptive signal processing are covered in first two chapters of dissertation. The approach of this thesis is not based on one methodology but several algorithms and configurations that are proposed and examined to fight the ISI problem. There are two main categories of channel equalization techniques, supervised (training) and blind unsupervised (blind) modes. We have studied the application of a new and specially modified neural network requiring very short training period for the proper channel equalization in supervised mode. The promising performance in the graphs for this network is presented in chapter 4. For blind modes two distinctive methodologies are presented and studied. Chapter 3 covers the concept of multiple cooperative algorithms for the cases of two and three cooperative algorithms. The select absolutely larger equalized signal and majority vote methods have been used in 2-and 3-algoirithm systems respectively. Many of the demonstrated results are encouraging for further research. Chapter 5 involves the application of general concept of simulated annealing in blind mode equalization. A limited strategy of constant annealing noise is experimented for testing the simple algorithms used in multiple systems. Convergence to local stationary points of the cost function in parameter space is clearly demonstrated and that justifies the use of additional noise. The capability of the adding the random noise to release the algorithm from the local traps is established in several cases

Design of Mobile Radio Channel Simulators Using the Iterative Nonlinear Least Square Approximation Method with Applications in Vehicle-to-X Communications

Doktorgradsavhandling i informasjons- og kommunikasjonsteknologi, Universitetet i Agder, 2015Vehicle-to-X (V2X) communication systems are expected to provide tremendous benefits associated with the safety and traffic efficiency on roads. The successful deployment of emerging technologies like V2X requires channel models accurately representing fading statistics in environments where those technologies are used. The accuracy is, of course, a major concern when adapting or developing a suitable channel model for test and evaluation purposes. However, it is also important to take into account the simplicity of a channel model, which is crucial for efficient numerical computations and computer simulations. Reconciling simplicity and accuracy is a rather complex task to accomplish, which requires sophisticated parameter computation methods. To the best of our knowledge, only a limited number of investigations address the channel modelling and parametrization problems for vehicular propagation scenarios in the literature. In order to fill this gap, we concentrate on the development of new sophisticated channel modelling approaches and efficient parameter computation methods for the design of V2X communication systems in this dissertation. In general, there are two main applications of channel models: (1) for the design and test of wireless communication systems and (2) for the optimization of existing communication systems. For the design and test purposes, more general statistical models such as Rice and Rayleigh channel models are preferred. Those channel models provide a fundamental insight into propagation phenomena and at the same time they greatly simplify the theoretical and numerical computations to assess the performance of wireless communication systems. For the optimization purposes, however, measurement-based channel models are commonly used. The main advantage of such channel models is that they always accurately reflect the physical reality. In this dissertation, we will focus on the channel models designed for both of those application purposes. A significant part of this dissertation will be devoted to the thorough analysis and design of Rayleigh and Rice fading channel models. We investigate the correlation properties of those channels assuming asymmetrical shapes of Doppler power spectral densities (PSDs). In fact, this is what we often observe in real-world propagation scenarios. In this regard, we will present an analytical expression for the autocorrelation function (ACF) of Rice processes that captures such realistic scenarios. Another important contribution to this topic is the novel iterative nonlinear least square approximation method for the design of Rice and Rayleigh channel simulators based on sum-of-sinusoids (SOS), as well as sum-of-cisoids (SOC) approaches. The idea behind the proposed method is very simple. The parameters of the simulation model are extracted from the reference model, such as the stochastic Rice and Rayleigh channel models, by fitting the statistical properties of interest, e.g. the ACF and the probability density function (PDF). We show that the proposed method outperforms several other methods in designing channel simulators with desired distribution and correlation properties. We also show that the proposed method provides a subtle balance between channel model’s simplicity and accuracy in designing Rayleigh and Rice channel simulators. The parametrization is a process of determining the key parameters specifying the channel model. This process has a great influence on the reliability of the developed channel model. It is therefore highly desirable if those parameters are extracted from measurements. In fact, this idea constitutes the fundamental concept behind measurement-based channel modelling approach. The measurement-based models are important in the sense that they can be used for the optimizations of the wireless communication system. Hence, the problem of computing the channel model parameters from the measurements is of special interest. In this regard, we propose iterative nonlinear least square approximation method for the design of measurementbased channel simulators. Through detailed investigations and comparative studies, we demonstrate that the proposed method is highly flexible and outperforms several other conventional methods in terms of reproducing the correlation characteristics obtained from several measurements. In addition, we introduce a new approach for the design of channel models for V2X communications in tunnel environments, where the number of scatterers contributing to the total received power is relatively small

Importance Sampling for Objetive Funtion Estimations in Neural Detector Traing Driven by Genetic Algorithms

To train Neural Networks (NNs) in a supervised way, estimations of an objective function must be carried out. The value of this function decreases as the training progresses and so, the number of test observations necessary for an accurate estimation has to be increased. Consequently, the training computational cost is unaffordable for very low objective function value estimations, and the use of Importance Sampling (IS) techniques becomes convenient. The study of three different objective functions is considered, which implies the proposal of estimators of the objective function using IS techniques: the Mean-Square error, the Cross Entropy error and the Misclassification error criteria. The values of these functions are estimated by IS techniques, and the results are used to train NNs by the application of Genetic Algorithms. Results for a binary detection in Gaussian noise are provided. These results show the evolution of the parameters during the training and the performances of the proposed detectors in terms of error probability and Receiver Operating Characteristics curves. At the end of the study, the obtained results justify the convenience of using IS in the training

Optimisation of wireless communication system by exploitation of channel diversity

Communication systems are susceptible to degradation in performance because of interference received through their side lobes. The interference may be deliberate electronic counter measure (ECM), Accidental RF Interference (RFI) or natural noise. The growth of interference communication systems have given rise to different algorithms, Adaptive array techniques offer a possible solution to this problem of interference received through side lobes because of their automatic null steering in both spatial and frequency domains. Key requirement for space-time architecture is to use robust adaptive algorithms to ensure reliable operation of the smart antenna. Space division multiple access (SDMA) involves the use of adaptive nulling to allow two or more users (mobiles) in the same cell to share same frequency and time slot. One beam is formed for each user with nulls in the direction of other users. Different approaches have been used to identify the interferer from desired user. Thus a basic model for determining the angle of arrival of incoming signals, an appropriate antenna beam forming and adaptive algorithms are used for array processing. There is an insatiable demand for capacity in wireless data networks and cellular radio communication systems. However the RF environment that these systems operate in is harsh and severely limits the capacity of traditional digital wireless networks. With normal wireless systems this limits the data rate in cellular radio environments to approximately 200 kbps whereas much higher data rates in excess of 25Mbps are required. A common wireless channel problem is that of frequency selective multi-path fading. To combat this problem, new types of wireless interface are being developed which utilise space, time and frequency diversity to provide increasing resilience to the channel imperfections. At any instant in time, the channel conditions may be such that one or more of these diversity methods may offer a superior performance to the other diversity methods. The overall aim of the research is to develop new systems that use a novel combination of smart antenna MIMO techniques and an advanced communication system based on advanced system configuration that could be exploited by IEEE 802.20 user specification approach for broadband wireless networking. The new system combines the Multi-input Multi-output communication system with frequency diversity in the form of an OFDM modulator. The benefits of each approach are examined under similar channel conditions and results presented.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

MIMO channel modelling and simulation for cellular and mobile-to-mobile

Recently, mobile-to-mobile (M2M) communications have received much attention due to several emerging applications, such as wireless mobile ad hoc networks, relay-based cellular networks, and dedicated short range communications (DSRC) for intelligent transportation systems (e.g., IEEE 802.11p standard). Different from conventional fixed-to-mobile (F2M) cellular systems, in M2M systems both the transmitter (Tx) and receiver (Rx) are in motion and often equipped with low elevation antennas. Multiple-input-multiple-output (MIMO) technologies, employing multiple antennas at both the Tx and Rx, have widely been adopted for the third generation (3G) and beyond-3G (B3G) F2M cellular systems due to their potential benefits of improving coverage, link reliability, and overall system capacity. More recently, MIMO has been receiving more and more attention for M2M systems as well. Reliable knowledge of the propagation channel obtained from channel measurements and corresponding channel models serve as the enabling foundation for the design and analysis of MIMO F2M and M2M systems. Furthermore, the development of accurate MIMO F2M and M2M channel simulation models plays a major role in the practical simulation and performance evaluation of these systems. These form the primary motivation behind our research on MIMO channel modelling and simulation for F2M cellular and M2M communication systems. In this thesis, we first propose a new wideband theoretical multiple-ring based MIMO regular-shaped geometry-based stochastic model (RS-GBSM) for non-isotropic scattering F2M macro-cell scenarios and then derive a generic space-time-frequency (STF) correlation function (CF). The proposed theoretical reference wideband model can be reduced to a narrowband one-ring model, a new closed-form STF CF of which is derived as well. Narrowband and wideband sum-of-sinusoids (SoS) simulation models are then developed, demonstrating a good agreement with the corresponding reference models in terms of correlation functions. Secondly, based on a well-known narrowband two-ring single-input single-output (SISO) M2M channel reference model, we propose new deterministic and stochastic SoS simulation models for non-isotropic scattering environments. The proposed deterministic simulator is the first SISO M2M deterministic simulator with good performance, while the proposed stochastic simulator outperforms the existing one in terms of fitting the desired statistical properties of the corresponding reference model. Thirdly, a new adaptive narrowband MIMO M2M RS-GBSM is proposed for nonisotropic scattering environments. To the best of our knowledge, the proposed M2M model is the first RS-GBSM that has the ability to study the impact of the vehicular traffic density on channel statistics. From the proposed theoretical reference model, we comprehensively investigate some important M2M channel statistics including the STF CF, space-Doppler-frequency power spectral density, envelope level crossing rate, and average fade duration. A close agreement between some channel statistics obtained from the proposed reference model and measurement data is observed, confirming the utility of our model. Finally, we extend the above narrowband model to a new wideband MIMO M2M RSGBSM with respect to the frequency-selectivity. The proposed wideband reference model is validated by observing a good match between some statistical properties of the theoretical model and available measurement data. From the wideband reference model, we further design new wideband deterministic and stochastic SoS simulation models. The proposed wideband simulators can be easily reduced to narrowband ones. The utilities of the newly derived narrowband and wideband simulation models are validated by comparing their statistical properties with those of the corresponding reference models. The proposed channel reference models and simulators are expected to be useful for the design, testing, and performance evaluation of future MIMO cellular and M2M communication systems.Scottish Funding Counci

Design and analysis of wireless diversity system

Ph.DDOCTOR OF PHILOSOPH