106 research outputs found

    MIMO techniques for higher data rate wireless communications

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    The demand for higher data rate, higher spectral efficiency and better quality of service in wireless communications is growing fast in the past few years. However, obtaining these requirements become challenging for wireless communication systems due to the problems of channel multi-path fading, higher power loss and power bandwidth limitations. A lot of research interest has been directed towards implementing new techniques in wireless communication systems, such as MIMO an OFDM, to overcome the above mentioned problems. Methods of achieving higher data rate and better spectral efficiency have been dealt with in the thesis. The work comprised three parts; the first part focuses on channel modelling, the second looks at fading mitigation techniques, and the third part deals with adaptive transmission schemes for different diversity techniques. In the first part, we present multiple-input multiple-output (MIMO) space-time geometrical channel model with hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment. The model is based on one-ring scattering assumption. This MIMO model provides statistics of the time of arrival (TOA) and direction of arrival (DOA). Our analytical results are validated with measurement data and compared to different geometrical based signal bounce macro-cell (GBSSBM) channel models including Gaussian scatterer density (GSD) channel model, the geometrical based exponential (GBE) channel model. On the other hand, for the same channel model we investigate the analytical methods which capture physical wave and antenna configuration at both ends representing in a matrix form. In the second part, we investigate the proposed channel model using joint frequency and spatial diversity system. . We combine STBC with OFDM to improve the error performance in the fading channels. We consider two different fading scenarios namely frequency selective and time selective fading channels. For the first scenario we propose a new technique to suppress the frequency error offset caused by the motion of mobile (Doppler shift). On the other hand, we examine the performance of STBC-OFDM in time selective macro-cell channel environment. In the last part, we evaluate the spectral efficiency for different receiver diversity namely maximal ratio combiner (MRC), selection combiner (SC), and Hybrid (MRC/SC). We derive closed form expressions for the single user capacity, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying spatially independent flat Rayleigh fading channel. Three adaptive transmission schemes are analysed: 1) optimal power rate and rate adaptation (opra), constant power with optimal rate adaptation (ora), and 3) channel inversion with fixed rate (cifr). Furthermore, we derive analytical results for capacity statistics including moment generating function (MGF), complementary cumulative distribution function (CDF) and probability density function (pdf)

    Characterisation and Modelling of Indoor and Short-Range MIMO Communications

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    Over the last decade, we have witnessed the rapid evolution of Multiple-Input Multiple-Output (MIMO) systems which promise to break the frontiers of conventional architectures and deliver high throughput by employing more than one element at the transmitter (Tx) and receiver (Rx) in order to exploit the spatial domain. This is achieved by transmitting simultaneous data streams from different elements which impinge on the Rx with ideally unique spatial signatures as a result of the propagation paths’ interactions with the surrounding environment. This thesis is oriented to the statistical characterisation and modelling of MIMO systems and particularly of indoor and short-range channels which lend themselves a plethora of modern applications, such as wireless local networks (WLANs), peer-to-peer and vehicular communications. The contributions of the thesis are detailed below. Firstly, an indoor channel model is proposed which decorrelates the full spatial correlation matrix of a 5.2 GHzmeasuredMIMO channel and thereafter assigns the Nakagami-m distribution on the resulting uncorrelated eigenmodes. The choice of the flexible Nakagami-m density was found to better fit the measured data compared to the commonly used Rayleigh and Ricean distributions. In fact, the proposed scheme captures the spatial variations of the measured channel reasonably well and systematically outperforms two known analytical models in terms of information theory and link-level performance. The second contribution introduces an array processing scheme, namely the three-dimensional (3D) frequency domain Space Alternating Generalised Expectation Maximisation (FD-SAGE) algorithm for jointly extracting the dominant paths’ parameters. The scheme exhibits a satisfactory robustness in a synthetic environment even for closely separated sources and is applicable to any array geometry as long as its manifold is known. The algorithm is further applied to the same set of raw data so that different global spatial parameters of interest are determined; these are the multipath clustering, azimuth spreads and inter-dependency of the spatial domains. The third contribution covers the case of short-range communications which have nowadays emerged as a hot topic in the area of wireless networks. The main focus is on dual-branch MIMO Ricean systems for which a design methodology to achieve maximum capacities in the presence of Line-of-Sight (LoS) components is proposed. Moreover, a statistical eigenanalysis of these configurations is performed and novel closed-formulae for the marginal eigenvalue and condition number statistics are derived. These formulae are further used to develop an adaptive detector (AD) whose aim is to reduce the feasibility cost and complexity of Maximum Likelihood (ML)-based MIMO receivers. Finally, a tractable novel upper bound on the ergodic capacity of the above mentioned MIMO systems is presented which relies on a fundamental power constraint. The bound is sufficiently tight and applicable for arbitrary rank of the mean channel matrix, Signal-to-Noise ratio (SNR) and takes the effects of spatial correlation at both ends into account. More importantly, it includes previously reported capacity bounds as special cases

    Developing and Utilizing Multivariate Stochastic Wireless Channel Models

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    Title from PDF of title page viewed June 20, 2019Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 84-92)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2019Developing accurate channel models is paramount in designing efficient mobile communication systems. The focus of this dissertation is to understand the small-scale fading characteristics, develop mathematical tools that accurately capture these characteristics and utilize them in three different applications - diversity receivers, scheduling, packet duplication in dual connectivity scenarios. This dissertation develops multivariate stochastic models for Rayleigh fading channels that incorporate factors such as the velocity of the users, angle of arrival distribution of signals, and carrier frequency. The developed models are more comprehensive than the existing ones. They capture the correlation characteristics of signals more accurately and are applicable to more practical scenarios. The developed models are the only ones that incorporate the spatial correlation structure suggested by 3GPP. The models are used to derive analytical expressions for the output SNR of certain diversity receivers. Owing to our expressions, the output SNR performances of these receivers are now studied through their moments. The moments provide insight about the nature of these receivers’ output SNR distribution, which is very useful in their reliability analysis. Secondly, the models are used to capture the temporal evolution of the received iii SNR. Temporal correlation characteristics of the SNR are exploited to decrease the number of variables in the downlink scheduling problem. This is achieved by making scheduling decisions less frequently for users with relatively higher coherence time. The results illustrate that the number of operations it takes to make scheduling decisions can be reduced by 33% with confidence probability of 0.7 and by 58% with confidence probability of 0.4. Finally, fade duration and non-fade duration characteristics of a Rayleigh fading channel are used to partially and randomly duplicate some packets when connected to multiple base stations. This is performed based on the small-scale fading statistics rather than the large-scale fading. Duplication based on large time scales can be wasteful and unnecessary, so it is shown using matrix exponential distributions how with low complexity to duplicate only when necessary. The results indicate that up to 50% of the resources at the duplicating base station can be liberated whilst meeting the target reliability measure.Introduction -- Moments of the Quadrivariate Rayleigh Distribution with applications for diversity receivers -- Reducing computational time of a wireless resource scheduler by exploiting temporal channel characteristics -- Partial packet duplication in 5G: control of fade and non-fade duration outages using matrix exponential distributions -- Conclusion and future work -- Appendix A. Derivation of the PDF of the Quadrivariate Rayleigh Distribution -- Appendix B. Derivation of the CDF of the Quadrivariate Rayleigh Distribution -- Appendix C. Derivation of the MGF of the Quadrivariate Rayleigh Distribution -- Appendix D. Derivation of bivariate SNR density -- Appendix E. Derivation of trivariate distribution density of Rayleigh Random variable

    Statistical Analysis of Coherent Monostatic and Bistatic Radar Sea Clutter

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    Radar sea clutter analysis has been an important area of radar research for many years. Very limited research has been carried out on coherent monostatic sea clutter analysis and even less on bistatic sea clutter. This has left a significant gap in the global scientific knowledge within this area. This thesis describes research carried out to analyse, quantify and model coherent sea clutter statistics from multiple radar sources. The ultimate goal of the research is to improve maritime radars' ability to compensate for clutter and achieve effective detection of targets on or over the sea surface. The first analyses used monostatic data gathered during the fight trials of the Thales Searchwater 2000 AEW radar. A further sea clutter trials database from CSIR was then used to investigate the variation of clutter statistics with look angle and grazing angle. Finally simultaneous monostatic and bistatic sea clutter data recorded in South Africa using the S-band UCL radar system NetRAD were analysed. No simultaneous monostatic and bistatic coherent analysis has ever been reported before in the open literature. The datasets recorded included multiple bistatic angles at both horizontal and vertical polarisations. Throughout the analysis real data have been compared to accepted theoretic models of sea clutter. An additional metric of comparison was investigated relating to the area of information theoretic techniques. Information theory is a significant subject area, and some concepts from it have been applied in this research. In summary this research has produced quantifiable and novel results on the characteristics of sea clutter statistics as a function of Doppler. Analysis has been carried out on a wide range of monostatic and bistatic data. The results of this research will be extremely valuable in developing sea clutter suppression algorithms and thus improving detection performance in future maritime radar designs

    On the Fundamentals of Stochastic Spatial Modeling and Analysis of Wireless Networks and its Impact to Channel Losses

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    With the rapid evolution of wireless networking, it becomes vital to ensure transmission reliability, enhanced connectivity, and efficient resource utilization. One possible pathway for gaining insight into these critical requirements would be to explore the spatial geometry of the network. However, tractably characterizing the actual position of nodes for large wireless networks (LWNs) is technically unfeasible. Thus, stochastical spatial modeling is commonly considered for emulating the random pattern of mobile users. As a result, the concept of random geometry is gaining attention in the field of cellular systems in order to analytically extract hidden features and properties useful for assessing the performance of networks. Meanwhile, the large-scale fading between interacting nodes is the most fundamental element in radio communications, responsible for weakening the propagation, and thus worsening the service quality. Given the importance of channel losses in general, and the inevitability of random networks in real-life situations, it was then natural to merge these two paradigms together in order to obtain an improved stochastical model for the large-scale fading. Therefore, in exact closed-form notation, we generically derived the large-scale fading distributions between a reference base-station and an arbitrary node for uni-cellular (UCN), multi-cellular (MCN), and Gaussian random network models. In fact, we for the first time provided explicit formulations that considered at once: the lattice profile, the users’ random geometry, the spatial intensity, the effect of the far-field phenomenon, the path-loss behavior, and the stochastic impact of channel scatters. Overall, the results can be useful for analyzing and designing LWNs through the evaluation of performance indicators. Moreover, we conceptualized a straightforward and flexible approach for random spatial inhomogeneity by proposing the area-specific deployment (ASD) principle, which takes into account the clustering tendency of users. In fact, the ASD method has the advantage of achieving a more realistic deployment based on limited planning inputs, while still preserving the stochastic character of users’ position. We then applied this inhomogeneous technique to different circumstances, and thus developed three spatial-level network simulator algorithms for: controlled/uncontrolled UCN, and MCN deployments

    Bearing estimation techniques for improved performance spread spectrum receivers

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    The main topic of this thesis is the use of bearing estimation techniques combined with multiple antenna elements for spread spectrum receivers. The motivation behind this work is twofold: firstly, this type of receiver structure may offer the ability to locate the position of a mobile radio in an urban environment. Secondly, these algorithms permit the application of space division multiple access (SDMA) to cellular mobile radio, which can offer large system capacity increases. The structure of these receivers may naturally be divided into two parts: signal detection and spatial filtering blocks. The signal detection problem involves locating the bearings of the multipath components which arise from the transmission of the desired user’s signal. There are a number of approaches to this problem, but here the MUSIC algorithm will be adopted. This algorithm requires an initial estimate of the number of signals impinging on the receiver, a task which can be performed by model order determination techniques. A major deficiency of MUSIC is its inability to resolve the highly–correlated and coherent multipath signals which frequently occur in a spread spectrum system. One of the simplest ways to overcome this problem is to employ spatial smoothing techniques, which trade the size of the antenna array for the ability to resolve coherent signals. The minimum description length (MDL) is one method for determining the signal model order and it can easily be extended to calculating the required degree of spatial smoothing. In this thesis, an approach to analysing the probability of correct model order determination for the MDL with spatial smoothing is presented. The performance of MUSIC, combined with spatial smoothing, is also of great significance. Two smoothing algorithms, spatial smoothing and forward–backward spatial smoothing, are analysed to compare their performance. If SDMA techniques are to be deployed in cellular systems, it is important to first estimate the performance improvements available from applying antenna array spatial filters. Initially, an additive white Gaussian noise channel is used for estimating the capacity of a perfect power–controlled code division multiple access system with SDMA techniques. Results suggest that the mean interference levels are almost halved as the antenna array size doubles, permitting large capacity increases. More realistic multipath models for urban cellular radio channels are also considered. If the transmitter gives rise to a number of point source multipath components, the bearing estimation receiver is able to capture the signal energy of each multipath. However, when a multipath component has significant angular spread, bearing estimation receivers need to combine separate directional components, at an increased cost in complexity, to obtain similar results to a matched filter. Finally, a source location algorithm for urban environments is presented, based on bearing estimation of multipath components. This algorithm requires accurate knowledge of the positions of the major multipath reflectors present in the environment. With this knowledge it is possible to determine the position of a transmitting mobile unit. Simulation results suggest that the algorithm is very sensitive to angular separation of the multipath components used for the source location technique

    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

    Detection and motion parameters estimation techniques in Forward Scatter Radar

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    Forward scatter Radar systems designed to take advantage of the greater radar cross section, that is robust to Radar Absorbing Material and other stealth technology, and of the long integration times, due to the little phase and amplitude fluctuations, are attractive for a variety of applications. Many of which fit well with the needs of augmentation of the surveillance capabilities of low-observable targets that may have a small backscatter RCS when observed with the conventional radar systems. This thesis reports on research into this field of radar systems with additional contributions to target detection and motion parameters estimation. Particularly, the first part of the thesis deals with the detection of moving targets that follow a linear trajectory in a single node FSR configuration. The detection scheme based on a square-law detector followed by an appropriate matched filter, here addressed as Crystal Video Detector (CVD) following the traditional terminology (Crystal Video Receiver), has already been put forward in the literature. Performance prediction and FSR system design were key motivator to analytically characterize the detection performance of CVD in terms of both, probability of false alarm and probability of detection. The derived closed-form expressions were validate from Monte Carlo simulations under different geometrical conditions and from experimental data acquired by a passive FSR based on FM signals. Furthermore, new detection schemes based on the CVD ensuring the constant false alarm rate (CFAR) condition were devised and analytically characterized. The performance analysis showed quite small losses of the CFAR-CVD detectors compared to the fixed threshold CVD. The second part of the thesis still handles the problem of target detection through the derivation of innovative detection schemes based on the Generalized Likelihood Ratio Test (GLRT). A comparison with the detection performance of the CVD has proven the better performance of the GLRT-based detectors. In most cases the improvement has an upper bound of 3 dB. However, there are specific circumstances where the standard FSR detector shows significant losses while the GLRT schemes suffer a much smaller degradation. Moreover the possibility to have a set of secondary data assumed target free, drove to the devising of new GLRT schemes. The results demonstrated a non-negligible further improvement over the previous GLRT schemes when the operation conditions get close to the near field transition point. The detection performance of the derived detectors without and with secondary data were analytically characterized. This analytical performance allowed to derive simplified equivalent SNR expressions that relate the GLRT detection performance to the main system and target parameters. These expressions showed to be useful for the design of effective FSR geometries that guarantee desired detection performance for specific targets. In the third part of the thesis the focus is moved to the motion parameters estimation through both, a single baseline and a dual baseline FSR configuration. Accordingly, the Doppler signature extracted from the Crystal Video based scheme is exploited. Following motion parameters estimation approaches already introduced in the literature, a two dimensional filter bank technique was proposed. The main target parameters encoding Doppler rate, main lobe width and crossing time instant were estimated from such technique. The accuracy of the proposed technique was investigated from a theoretical point of view through the derivation of simplified closed-form expression of the Cramer Rao Lower Bound (CRLB). The analysis proved that unbiased estimates of the desired target parameters can be obtained that approach the derived CRLB in the high SNR region. After the dependence of the kinematic parameters on the parameters estimated from the bank was exploited. The cross baseline velocity in a single baseline configuration was estimated under the assumption that the baseline crossing point is known. Meanwhile the dual baseline configuration ensures the possibility to estimate also the baseline crossing point without a priori knowledge on the other target kinematic parameters. Once more, the CRLB of the target motion parameters for both reference scenarios was derived. The analysis proved that unbiased estimates of the target motion parameters can be obtained with high accuracy even for low SNR conditions. The effectiveness of the proposed approach was also shown from experimental data acquired by a passive FSR based on FM signals
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