8 research outputs found

    A new stochastic spatio-temporal propagation model (SSTPM) for mobile communications with antenna arrays

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    Characterization of MIMO channel capacity in urban microcellular environment

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    The research work in this thesis consists of several investigations of multiple-input multiple-output (MIMO) wireless channel capacity in urban microcellular environment. The investigations can be categorized into three groups, 1)- model-based investigations, 2)- measurement-based investigations, and 3)- theoretical investigations. Utilizing three dimensional (3D) channel models the influence of environment physical parameters and antenna array configuration on MIMO channel capacity are investigated. In terms of environment influence, parameters such as street width, wall relative permittivity and multipath richness are considered. In terms of antenna array configuration, the effect of array geometry and uniform linear array (ULA) azimuthal orientation are considered. It is shown that the effect of these parameters on MIMO channel capacity is significant. Based on field measurements, the effect of spatial smoothing on the accuracy of a widely used stochastic narrowband MIMO radio channel model, namely, the Kronecker model, and the impact of temporal signal to noise ratio (SNR) variations on MIMO channel capacity are investigated. Results from non-line of sight (NLOS) and line of sight (LOS) propagation scenarios are analyzed. While under NLOS conditions spatial smoothing significantly enhances the applicability of the Kronecker structure, under LOS conditions spatial smoothing does not help to improve the accuracy of the Kronecker model. It is also noticed that while the temporal SNR variation has significant impact on the capacity of MIMO wireless channel in a NLOS propagation scenario, the influence is smaller under LOS conditions. Theoretical investigation of antenna mutual coupling (MC) on the capacity of MIMO wireless channels is presented with particular emphasis on the case of high SNR scenario. It is shown that the effect of MC on MIMO channel capacity can be positive or negative depending on the spatial correlation properties of the propagation environment and the characteristics of the two ends MC matrices. The impact of phase noise (PN) on the accuracy of measured MIMO channel capacity is studied by considering its effect on both the spatial multiplexing gain and the power gain. It is shown that in the case of a low rank physical channel matrix the PN impact is more pronounced on the spatial multiplexing gain than on the power gain. Based on that an eigenvalue filtering (EVF) technique is proposed to improve the accuracy of the measured MIMO channel capacity.reviewe

    Cyclic Prefix-Free MC-CDMA Arrayed MIMO Communication Systems

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    The objective of this thesis is to investigate MC-CDMA MIMO systems where the antenna array geometry is taken into consideration. In most MC-CDMA systems, cyclic pre xes, which reduce the spectral e¢ ciency, are used. In order to improve the spectral efficiency, this research study is focused on cyclic pre x- free MC-CDMA MIMO architectures. Initially, space-time wireless channel models are developed by considering the spatio-temporal mechanisms of the radio channel, such as multipath propaga- tion. The spatio-temporal channel models are based on the concept of the array manifold vector, which enables the parametric modelling of the channel. The array manifold vector is extended to the multi-carrier space-time array (MC-STAR) manifold matrix which enables the use of spatio-temporal signal processing techniques. Based on the modelling, a new cyclic pre x-free MC- CDMA arrayed MIMO communication system is proposed and its performance is compared with a representative existing system. Furthermore, a MUSIC-type algorithm is then developed for the estimation of the channel parameters of the received signal. This proposed cyclic pre x-free MC-CDMA arrayed MIMO system is then extended to consider the effects of spatial diffusion in the wireless channel. Spatial diffusion is an important channel impairment which is often ignored and the failure to consider such effects leads to less than satisfactory performance. A subspace-based approach is proposed for the estimation of the channel parameters and spatial spread and reception of the desired signal. Finally, the problem of joint optimization of the transmit and receive beam- forming weights in the downlink of a cyclic pre x-free MC-CDMA arrayed MIMO communication system is investigated. A subcarrier-cooperative approach is used for the transmit beamforming so that there is greater flexibility in the allocation of channel symbols. The resulting optimization problem, with a per-antenna transmit power constraint, is solved by the Lagrange multiplier method and an iterative algorithm is proposed

    Geometry-based stochastic physical channel modeling for cellular environments

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    Telecommunication has experienced significant changes over the past few years and its paradigm has moved from wired to wireless communications. The wireless channel constitutes the basic physical link between the transmitter and the receiver antennas. Therefore, complete knowledge of the wireless channel and radio propagation environment is necessary in order to design efficient wireless communication systems. This PhD thesis is devoted to studying the spatial and temporal statistics of the wireless channel in cellular environments based on a geometry-based stochastic physical channel modeling approach. Contributions in this thesis report include the following: • A new physical channel model called the eccentro-scattering model is proposed to study the spatial and temporal statistics of the multipath signals in cellular environments. • Generic closed-form formulas for the probability density function (pdf) of angle of arrival (AoA) and time of arrival (ToA) of the multipath signals in each cellular environment are derived. These formulas can be helpful for the design and evaluation of modern communication systems. • A new Gaussian scattering model is proposed, which consists of two Gaussian functions for the distribution of scatterers around base station (BS) and mobile station (MS) and confines these scatterers within a scattering disc. • The effect of mobile motion on the spatial and temporal statistics of the multipath signals in cellular environments is discussed. Three motion scenarios are considered for the possible trajectory of the mobile unit. Furthermore, two different cases are identified when the terrain and clutter of mobile surrounding have additional effect on the temporal spread of the multipath signals during motion. • The physical channel model is employed to assess the performance of a RAKE receiver in cellular environments. • Comparisons between uniform scattering and Gaussian scattering, which are the two assumptions for the distribution of scatterers usually used in the derivation of the pdf of AoA, are also presented. • An overview of earlier physical channel models and comparisons between these models and with the proposed model are presented

    Spatial diversity in MIMO communication systems with distributed or co-located antennas

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    The use of multiple antennas in wireless communication systems has gained much attention during the last decade. It was shown that such multiple-input multiple-output (MIMO) systems offer huge advantages over single-antenna systems. Typically, quite restrictive assumptions are made concerning the spacing of the individual antenna elements. On the one hand, it is typically assumed that the antenna elements at transmitter and receiver are co-located, i.e., they belong to some sort of antenna array. On the other hand, it is often assumed that the antenna spacings are sufficiently large, so as to justify the assumption of independent fading. In this thesis, the above assumptions are relaxed. In the first part, it is shown that MIMO systems with distributed antennas and MIMO systems with co-located antennas can be treated in a single, unifying framework. In the second part this fact is utilized, in order to develop appropriate transmit power allocation strategies for co-located and distributed MIMO systems. Finally, the third part focuses on specific synchronization problems that are of interest for distributed MIMO systems

    Recent Advances in Signal Processing

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    The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

    A new stochastic spatio-temporal propagation model (SSTPM) for mobile communications with antenna arrays

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