No / A novel printed diversity monopole antenna is presented for WiFi/WiMAX applications. The antenna comprises two crescent shaped radiators placed symmetrically with respect to a defected ground plane and a wideband zigzag neutralization line is connected between them to achieve good impedance matching and low mutual coupling. Theoretical and experimental characteristics are illustrated for this antenna, which achieves an impedance bandwidth of 54.5% (over 2.4 – 4.2 GHz), at a reflection coefficient < −10 dB, mutual coupling < −16 dB. An acceptable agreement is obtained for the computed and measured gain, radiation patterns, and envelope correlation coefficient. These characteristics demonstrate that the proposed antenna is an attractive candidate for the multiple input multiple output (MIMO) portable mobile devices.

Wireless optical MIMO links can achieve very high data transmission rates by exploiting spatial diversity at a grand scale. Although such links can achieve high rates, their practical implementation remains challenging. The difficulty in implementation arises due to the complex transmitter and receiver designs required to overcome the channel impairments. This thesis considers practical transmitter and receiver designs for the wireless optical MIMO channel in the presence of channel impairments. In the first part of the thesis, two techniques to improve channel capacity for wireless optical MIMO channels are presented. The first technique uses multilevel half toning to reduce quantization noise power. For quantization noise-limited systems, increasing the number of quantizer levels provides gains in capacity. For example, at a rate of 200fps, a four-level quantizer gives approximately a two-fold increase in capacity over a binary-level quantizer for all frame sizes considered. The second technique uses higher order noise shaping to shape the quantization noise to the out-of-band spatial frequency spectrum. This technique is shown to be useful when the number of levels is small, i.e., near 2. In the second part of the thesis, the receiver design for wireless optical MIMO channels with magnification is considered. The work done in this part constitute a step towards the practical implementation of such links since it is the first time the effects of spatial transformations are considered. Signal magnification introduces varying spatial frequency inter-channel interference (SF-ICI) at the receiver. A novel receiver design that uses complex windowing with decision feedback equalization is used to equalize the SF-ICI in spatial frequency domain. For SF-ICI limited channels, the novel receiver design achieved a low bit-error rate compared with rectangular windowing with zero-forcing equalization. However, for noise limited channels, rectangular windowing with zero-forcing equalization is the receiver design of choice. / Thesis / Master of Applied Science (MASc)

Yes / The present work investigates the operation performance of 2-element configuration multiple input Multiple Output (MIMO) antennas system using Cylindrical Dielectric Resonator (CDR). The MIMO antenna arrays achieve 22.2% impedance bandwidth at S11 ≤ -10 covering the bandwidth from 10GHz to 12.5GHz that meets the essential requirements of wide band communications applications. The first array gives a maximum isolation of 27dB at an element spacing of 22mm, whereas the second array presents a maximum isolation of 42.55dB at element spacing of 12.25mm.

Previous attempts to adapt MIMO systems in the presence of varying channel conditions typically focus on characterizing the performance of a limited and predefined set of joint MoDem/CoDec and MIMO configurations over a representative set of channel realizations. Other work has attempted to adapt only the MIMO scheme to varying channel conditions without considering modulation format or the channel code used. Finally, attempts to configure the system through direct BER calculation based on channel conditions were also proposed. These methods suffer the problems of dependence on a limited set of simulated curves which may not account for all channel conditions that a real system might see, not configuring all parameters jointly or implicitly requiring channel state information to be fed back to the transmitter. None of these previous attempts have handled both cases where CSIT is available or not while jointly configuring the MoDem, CoDec and multi-antenna scheme. This work consists of two parts, focusing on energy efficiency in the presence of unoccupied frequency bands and on spectrally efficient operation under static frequency assignment. Utilizing minimum Euclidean distances of MoDem constellations and the minimum free Hamming distance metrics for channel codes, we develop distance metrics to describe the MIMO schemes which are considered. A minimum required distance is then determined as a function of desired BER and constellation. Based on the unified set of distance metrics, adaptive algorithms can evaluate the total distance of a signaling scheme, including MoDem, CoDec and MIMO scheme, and then calculate a decision metric based on the total distance and the required distance to meet the desired BER. The proposed system which aims to maximize energy efficiency is able to choose, based on spatial correlation, available channels, CSIT availability, and power amplifier configuration, the appropriate multi-antenna configuration, MoDem and Codec to meet a fixed throughput requirement while maximizing the energy efficiency or robustness of the link. The proposed work assumes that the open channels of a network can be accessed through individually tunable RF chains of the multi-antenna systems. This assumption permits the use of a multi-antenna, multi-channel scheme which sacrifices spatial diversity for frequency diversity. In addition to traditional, single-channel transmit diversity schemes, the adaptive system is also able choose, when more energy efficient, this novel, multi-channel configuration. When focusing on the maximization of spectral efficiency, a more conventional, single-channel model is assumed. In addition to the distance metrics for single-channel diversity schemes, distance metrics are then developed for spatial multiplexing schemes which take into account the interaction of spatial correlation, number of antennas and the rate of the channel code. The adaptive system uses the total distance of the joint configuration of MoDem, CoDec and MIMO scheme to calculate a decision metric which indicates whether the configuration will meet the desired BER. From a list of joint configurations which will meet the desired BER, the adaptive system then chooses the one which maximizes the spectral efficiency. / Master of Science

<p>In recent years, multiple-input multiple-output (MIMO)systems appear to be very promising since they can provide highdata rates in environments with sucient scattering byexploiting the spatial domain. To design a real MIMO wirelesssystem and predict its performance under certain circumstances,it is necessary to have accurate MIMO wireless channel modelsfor dierent scenarios. This thesis presents dierent models forindoor MIMO radio propagation channels based on 5.2 GHz indoorMIMO channel measurements.The recent research on MIMO radio channel modeling isbriey reviewed in this thesis. The models are categorized intonon-physical and physical models. The non-physical modelsprimarily rely on the statistical characteristics of MIMOchannels obtained from the measured data while the physicalmodels describe the MIMO channel (or its distribution) via somephysical parameters. The relationships between dierent modelsare also discussed.For the narrowband case, a non line-of-sight (NLOS)indoor MIMO channel model is presented. The model is based on aKronecker structure of the channel covariance matrix and thefact that the channel is complex Gaussian. It is extended tothe line-of-sight (LOS) scenario by estimating and modeling thedominant component separately.As for the wideband case, two NLOS MIMO channel modelsare proposed. The rst model uses the power delay prole and theKronecker structure of the second order moments of each channeltap to model the wideband MIMO channel while the second modelcombines a simple single-input single-output (SISO) model withthe same Kronecker structure of the second order moments.Monte-Carlo simulations are used to generate indoor MIMOchannel realizations according to the above models. The resultsare compared with the measured data and good agreement has beenobserved.</p>

In recent years, multiple-input multiple-output (MIMO)systems appear to be very promising since they can provide highdata rates in environments with sucient scattering byexploiting the spatial domain. To design a real MIMO wirelesssystem and predict its performance under certain circumstances,it is necessary to have accurate MIMO wireless channel modelsfor dierent scenarios. This thesis presents dierent models forindoor MIMO radio propagation channels based on 5.2 GHz indoorMIMO channel measurements.The recent research on MIMO radio channel modeling isbriey reviewed in this thesis. The models are categorized intonon-physical and physical models. The non-physical modelsprimarily rely on the statistical characteristics of MIMOchannels obtained from the measured data while the physicalmodels describe the MIMO channel (or its distribution) via somephysical parameters. The relationships between dierent modelsare also discussed.For the narrowband case, a non line-of-sight (NLOS)indoor MIMO channel model is presented. The model is based on aKronecker structure of the channel covariance matrix and thefact that the channel is complex Gaussian. It is extended tothe line-of-sight (LOS) scenario by estimating and modeling thedominant component separately.As for the wideband case, two NLOS MIMO channel modelsare proposed. The rst model uses the power delay prole and theKronecker structure of the second order moments of each channeltap to model the wideband MIMO channel while the second modelcombines a simple single-input single-output (SISO) model withthe same Kronecker structure of the second order moments.Monte-Carlo simulations are used to generate indoor MIMOchannel realizations according to the above models. The resultsare compared with the measured data and good agreement has beenobserved. / <p>NR 20140805</p>

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第20741号 / 情博第655号 / 新制||情||113(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 原田 博司, 教授 守倉 正博, 教授 大木 英司 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

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Multi-antenna wireless systems have become very popular due to their theoretically predicted higher spectral efficiencies and improved performance compared to single-antenna systems. Large-scale multiple-input multiple-output (MIMO) systems refer to wireless systems where communication terminals employ tens to hundreds of antennas to achieve in-creased spectral efficiencies/sum rates, reliability, and power efficiency. Large-scale multi-antenna systems are attractive to meet the increasing wireless data rate requirements, without compromising on the bandwidth. This thesis addresses key signal processing issues in large-scale MIMO systems. Specifically, the thesis investigates efficient algorithms for signal detection and channel estimation in large-scale MIMO systems. It also investigates ‘spatial modulation,’ a multi-antenna modulation scheme that can reduce the number of transmit radio frequency (RF) chains, without compromising much on the spectral efficiency. The work reported in this thesis is comprised of the following two parts: 1 investigation of low-complexity receiver algorithms based on Markov chain Monte Carlo (MCMC) technique, tabu search, and belief propagation for large-scale uplink multiuser MIMO systems, and 2 investigation of achievable rates and signal detection in generalized spatial modulation. 1. Receiver algorithms for large-scale multiuser MIMO systems on the uplink In this part of the thesis, we propose low-complexity algorithms based on MCMC techniques, Gaussian sampling based lattice decoding (GSLD), reactive tabu search (RTS), and factor graph based belief propagation (BP) for signal detection on the uplink in large-scale multiuser MIMO systems. We also propose an efficient channel estimation scheme based on Gaussian sampling. Markov chain Monte Carlo (MCMC) sampling: We propose a novel MCMC based detection algorithm, which achieves near-optimal performance in large dimensions at low complexities by the joint use of a mixed Gibbs sampling (MGS) strategy and a multiple restart strategy with an efficient restart criterion. The proposed mixed Gibbs sampling distribution is a weighted mixture of the target distribution and uniform distribution. The presence of the uniform component in the sampling distribution allows the algorithm to exit from local traps quickly and alleviate the stalling problem encountered in conventional Gibbs sampling. We present an analysis for the optimum choice of the mixing ratio. The analysis approach is to define an absorbing Markov chain and use its property regarding the expected number of iterations needed to reach the global minima for the first time. We also propose an MCMC based algorithm which exploits the sparsity in uplink multiuser MIMO transmissions, where not all users are active simultaneously. Gaussian sampling based lattice decoding: Next, we investigate the problem of searching the closest lattice point in large dimensional lattices and its use in signal detection in large-scale MIMO systems. Specifically, we propose a Gaussian sampling based lattice decoding (GSLD) algorithm. The novelty of this algorithm is that, instead of sampling from a discrete distribution as in Gibbs sampling, the algorithm iteratively generates samples from a continuous Gaussian distribution, whose parameters are obtained analytically. This makes the complexity of the proposed algorithm to be independent of the size of the modulation alpha-bet. Also, the algorithm is able to achieve near-optimal performance for different antenna and modulation alphabet settings at low complexities. Random restart reactive tabu search (R3TS): Next, we study receiver algorithms based on reactive tabu search (RTS) technique in large-scale MIMO systems. We propose a multiple random restarts based reactive tabu search (R3TS) algorithm that achieves near-optimal performance in large-scale MIMO systems. A key feature of the proposed R3TS algorithm is its performance based restart criterion, which gives very good performance-complexity tradeoff in large-dimension systems. Lower bound on maximum likelihood (ML) bit error rate (BER) performance: We propose an approach to obtain lower bounds on the ML performance of large-scale MIMO systems using RTS simulation. In the proposed approach, we run the RTS algorithm using the transmitted vector as the initial vector, along with a suitable neighborhood definition, and find a lower bound on number of errors in ML solution. We demonstrate that the proposed bound is tight (within about 0.5 dB of the optimal performance in a 16×16MIMO system) at moderate to high SNRs. Factor graph using Gaussian approximation of interference (FG-GAI): Multiuser MIMO channels can be represented by graphical models that are fully/densely connected (loopy graphs), where conventional belief propagation yields suboptimal performance and requires high complexity. We propose a solution to this problem that uses a simple, yet effective, Gaussian approximation of interference (GAI) approach that carries out a linear per-symbol complexity message passing on a factor graph (FG) based graphical model. The proposed algorithm achieves near-optimal performance in large dimensions in frequency-flat as well as frequency-selective channels. Gaussian sampling based channel estimation: Next, we propose a Gaussian sampling based channel estimation technique for large-scale time-division duplex (TDD) MIMO systems. The proposed algorithm refines the initial estimate of the channel by iteratively detecting the data block and using that knowledge to improve the estimated channel knowledge using a Gaussian sampling based technique. We demonstrate that this algorithm achieves near-optimal performance both in terms of mean square error of the channel estimates and BER of detected data in both frequency-flat and frequency-selective channels. 2. Generalized spatial modulation In the second part of the thesis, we investigate generalized spatial modulation (GSM) in point-to point MIMO systems. GSM is attractive because of its ability to work with less number of transmit RF chains compared to traditional spatial multiplexing, without com-promising much on spectral efficiency. In this work, we show that, by using an optimum combination of number of transmit antennas and number of transmit RF chains, GSM can achieve better throughput and/or BER than spatial multiplexing. We compute tight bounds on the maximum achievable rate in a GSM system, and quantify the percentage savings in the number of transmit RF chains as well as the percentage increase in the rate achieved in GSM compared to spatial multiplexing. We also propose a Gibbs sampling based algorithm suited to detect GSM signals, which yields impressive BER performance and complexity results.

Le concept du radar MIMO est prometteur en raison des nombreux avantages qu'il apporte par rapport aux architectures radars actuelles : flexibilité pour la formation de faisceau à l'émission - large illumination de la scène et résolution fine après traitement - et allègement de la complexité des systèmes, via la réduction du nombre d'antennes et la possibilité de transférer des fonctions de contrôle et d'étalonnage du système dans le domaine numérique. Cependant, le radar MIMO reste au stade du concept théorique, avec une prise en compte insuffisante des impacts du manque d'orthogonalité des formes d'onde et des défauts matériels.Ce travail de thèse, dans son ambition de contribuer à ouvrir la voie vers le radar MIMO opérationnel, consiste à anticiper et compenser les défauts du monde réel par des traitements numériques. La première partie traite de l'élaboration des formes d'onde MIMO. Nous montrons que les codes de phase sont optimaux en termes de résolution spatiale. Nous présentons également leurs limites en termes d'apparition de lobes secondaires en sortie de filtre adapté. La seconde partie consiste à accepter les défauts intrinsèques des formes d'onde et proposer des traitements adaptés au modèle de signal permettant d'éliminer les lobes secondaires résiduels induits. Nous développons une extension de l'Orthogonal Matching Pursuit (OMP) qui satisfait les conditions opérationnelles, notamment par sa robustesse aux erreurs de localisation, sa faible complexité calculatoire et la non nécessité de données d'apprentissage. La troisième partie traite de la robustesse des traitements vis-à-vis des écarts au modèle de signal, et particulièrement la prévention et l'anticipation de ces phénomènes afin d'éviter des dégradations de performance. En particulier, nous proposons une méthode numérique d'étalonnage des phases des émetteurs. La dernière partie consiste à mener des expérimentations en conditions réelles avec la plateforme radar MIMO Hycam. Nous montrons que certaines distorsions subies non anticipées, même limitées en sortie de filtre adapté, peuvent impacter fortement les performances en détection des traitements dépendant du modèle de signal. / The MIMO radar concept promises numerous advantages compared to today's radar architectures: flexibility for the transmitting beampattern design - including wide scene illumination and fine resolution after processing - and system complexity reduction, through the use of less antennas and the possibility to transfer system control and calibration to the digital domain. However, the MIMO radar is still at the stage of theoretical concept, with insufficient consideration for the impacts of waveforms' lack of orthogonality and system hardware imperfections.The ambition of this thesis is to contribute to paving the way to the operational MIMO radar. In this perspective, this thesis work consists in anticipating and compensating the imperfections of the real world with processing techniques. The first part deals with MIMO waveform design and we show that phase code waveforms are optimal in terms of spatial resolution. We also exhibit their limits in terms of sidelobes appearance at matched filter output. The second part consists in taking on the waveform intrinsic imperfections and proposing data-dependent processing schemes for the rejection of the induced residual sidelobes. We develop an extension for the Orthogonal Matching Pursuit (OMP) that satisfies operational requirements, especially localization error robustness, low computation complexity, and nonnecessity of training data. The third part deals with processing robustness to signal model mismatch, especially how it can be prevented or anticipated to avoid performance degradation. In particular, we propose a digital method of transmitter phase calibration. The last part consists in carrying out experiments in real conditions with the Hycam MIMO radar testbed. We exhibit that some unanticipated encountered distortions, even when limited at the matched filter output, can greatly impact the performance in detection of the data-dependent processing methods.