The direct-sequence code division multiple access (DS-CDMA) is one of the significant techniques for wireless communication systems with multiple simultaneous transmissions. The main concern of this thesis is to propose a new linearly constrained constant modulus modified conjugate gradient (LCCM-MCG) adaptive filtering algorithm to deal with problem of channel mismatch associated with the multiple access interference (MAI) in DS-CDMA system over multipath fading channel. In fact, the adaptive filtering algorithm based on the CM criterion is known to be very attractive for the case when the channel parameters are not estimated perfectly. The proposed LCCM-MCG algorithm is derived based on the so-called generalized sidelobe canceller (GSC). It has the advantage of having better stability and less computational complexity compared with conventional recursive least-squares (RLS) algorithm, and can be used to achieve desired performance for multiuser RAKE receiver. Moreover, with the MCG algorithm it requires only one recursive iteration per incoming sample data for updating the weight vector, but still maintains performance comparable to the RLS algorithm. From computer simulation results, we show that the proposed LCCM-MCG algorithm has fast convergence rate and could be used to circumvent the effect due to channel mismatch. Also, the performance, in terms of bit error rate (BER), is quite close to the LCCM-RLS algorithm suggested in [18], and is superior to the stochastic gradient descent (SGD) algorithm proposed in [7].

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Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier transmission scheme used in most of the existing wireless standards such as LTE, WiFi and WiMAX. The popularity of OFDM stems from the multitude of benefits it offers in terms of providing high data rate transmission, robustness against multipath fading and ease of implementation. Additionally, OFDM signals are agile in the sense that any subcarrier can be switched on or off to fit the available transmission bandwidth, which makes it well suited for systems with dynamic spectrum access such as cognitive radio systems. Nonetheless, and despite all the aforementioned advantages, OFDM signals have high spectral sidelobes outside the designated band of transmission, that can create severe interference to users in adjacent transmission bands, particularly when there is no synchronization between users. The focus of this dissertation is to propose baseband solutions at the Physical Layer (PHY) of the communications system to address the interference resulting from the high out-of-band (OOB) emissions of OFDM. In the first part of this dissertation, we propose a precoder capable of generating mask compliant OFDM signals with low OOB emissions that are always contained under a given spectrum emission mask (SEM) specified by the OFDM standard. The proposed precoder generates transmitted signals with bit error rate (BER) performance similar to that of classical OFDM and does not reduce the spectral efficiency of the system. In the second part of this dissertation, we introduce a novel and elegant approach, called suppressing alignment (SA), to jointly reduce the OOB interference and peak-to-average power ratio (PAPR) of OFDM systems. SA exploits the unavoidable redundancy provided by the CP as well as the wireless communications channel to generate an OOB/PAPR suppressing signal at the OFDM transmitter. Furthermore, after passing through the wireless channel, the suppressing signal is aligned with the CP duration at the OFDM receiver, essentially causing no interference to the data portion of the OFDM symbol. The proposed approach improves the PAPR of the transmitted OFDM signal and reduces the OOB interference by tens of decibels. Additionally, the proposed approach maintains an error performance similar to that of plain OFDM without requiring any change in the receiver structure of legacy OFDM. In order to reduce the spectral emissions of OFDM, additional blocks, such as linear precoders, are usually introduced in the transmitter leading to a transmitted signal that is drastically different than that of a classical OFDM signal. This distortion is typically quantified by the error vector magnitude (EVM), a widely used metric specified by the wireless standard and is directly related to the BER performance of the system. The receiver can usually decode the information data with acceptable error probabilities if the distortion introduced to the transmitted signal is below the EVM values specified in the OFDM standard. Linear precoders, while capable of achieving significant reduction in the OOB interference, they typically introduce large distortion to the transmitted signal. As such, the receiver needs to know the precoding done at the transmitter to be able to recover the data which usually entails sending large amount of side information that can greatly reduce the spectral efficiency of the system. In the last part of this dissertation, we target the design of precoders for the purpose reducing the OOB interference, in a transparent manner where the receiver does not need to know the changes introduced in the transmitter. We present two precoders capable of significantly reducing the OOB emissions while producing transmitted signals with EVM values below those specified by the wireless standard, thereby guaranteeing acceptable error performance.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21108号 / 工博第4472号 / 新制||工||1695(附属図書館) / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 篠原 真毅, 教授 山川 宏, 教授 木本 恒暢 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

In aeroacoustic experiments of aircraft models and/or components, arrays of microphones are utilized to spatially isolate distinct sources and mitigate interfering noise which contaminates single-microphone measurements. Array measurements are still biased by interfering noise which is coherent over the spatial array aperture. When interfering noise is accounted for, existing algorithms which aim to both spatially isolate distinct sources and determine their individual levels as measured by the array are complex and require assumptions about the nature of the sound field. This work develops a processing scheme which uses spatially-defined phase constraints to remove correlated, interfering noise at the single-channel level. This is achieved through a merger of Conditioned Spectral Analysis (CSA) and the Generalized Sidelobe Canceller (GSC). A cross-spectral, frequency-domain filter is created using the GSC methodology to edit the CSA formulation. The only constraint needed is the user-defined, relative phase difference between the channel being filtered and the reference channel used for filtering. This process, titled Constrained Spectral Conditioning (CSC), produces single-channel Fourier Transform estimates of signals which satisfy the user-defined phase differences. In a spatial sound field mapping context, CSC produces sub-datasets derived from the original which estimate the signal characteristics from distinct locations in space. Because single-channel Fourier Transforms are produced, CSC's outputs could theoretically be used as inputs to many existing algorithms. As an example, data-independent, frequency-domain beamforming (FDBF) using CSC's outputs is shown to exhibit finer spatial resolution and lower sidelobe levels than FDBF using the original, unmodified dataset. However, these improvements decrease with Signal-to-Noise Ratio (SNR), and CSC's quantitative accuracy is dependent upon accurate modeling of the sound propagation and inter-source coherence if multiple and/or distributed sources are measured. In order to demonstrate systematic spatial sound mapping using CSC, it is embedded into the CLEAN algorithm which is then titled CLEAN-CSC. Simulated data analysis indicates that CLEAN-CSC is biased towards the mapping and energy allocation of relatively stronger sources in the field, which limits its ability to identify and estimate the level of relatively weaker sources. It is also shown that CLEAN-CSC underestimates the true integrated levels of sources in the field and exhibits higher-than-true peak source levels, and these effects increase and decrease respectively with increasing frequency. Five independent scaling methods are proposed for correcting the CLEAN-CSC total integrated output levels, each with their own assumptions about the sound field being measured. As the entire output map is scaled, these do not account for relative source level errors that may exist. Results from two airfoil tests conducted in NASA Langley's Quiet Flow Facility show that CLEAN-CSC exhibits less map noise than CLEAN yet more segmented spatial sound distributions and lower integrated source levels. However, using the same source propagation model that CLEAN assumes, the scaled CLEAN-CSC integrated source levels are brought into closer agreement with those obtained with CLEAN. / Ph. D.

In this thesis, a maximum likelihood receiver to obtain the target range profile that uses the clutter prediction derived from the target-free previous observations is suggested as a fast time processor for pulse compression radar systems. The maximum likelihood receiver is proposed to overcome the range sidelobe problem, which is introduced by the pulse compression method. Conventional methods, such as the matched filter receiver, as fast time processor result in the targets with high radar cross sec- tion masking the low radar cross section targets at the neighboring range cells / since sidelobes of the matched filter is determined by the autocorrelation of the spreading code and linearly proportional to target signal power. An unbiased estimator, like the maximum likelihood receiver in this thesis work does not su&crarr / er from such issues. In addition to that, to suppress the signal dependent interference, namely the clutter, at the output of fast time processor / the previous target-free observations are col- lected and utilized to predict the clutter signal for next time instant. This prediction is used in the maximum likelihood receiver. The clutter prediction is done for the stationary case and the internal clutter motion case, and their SINR performances with the maximum likelihood receiver are evaluated. In conclusion, such an approach managed to have an unbiased estimation of target range profile and the clutter suppression advantage in the fast time.

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Narrowband Internet-of-Things (NB-IoT) is a new wireless technology designed to support cellular networks with wide coverage for a massive number of very cheap low power user devices. Studies have been initiated for deployment of NB-IoT in unlicensed frequency bands, some of which demand the use of a frequency-hopping scheme with a short channel dwell time. In order for a device to connect to a cell, it must synchronize well within the dwell time in order to decode the frequency-hopping pattern. Due to the significant path loss, the narrow bandwidth and the device characteristics, decreasing the synchronization time is a challenge. This thesis studies different methods to decrease the synchronization time for NB-IoT without increasing the demands on the user device. The study shows how artificial fast fading can be combined with denser reference signalling in order to achieve improvements to the cell acquisition and synchronization procedure sufficient for enabling unlicensed operation of NB-IoT. / Narrowband Internet-of-Things (NB-IoT) är en ny trådlös teknik som är designad för att hantera mobilnät med vidsträckt täckning för ett massivt antal mycket billiga och strömsnåla användarenheter. Studier har inletts för att operera NB-IoT i olicensierade frekvensband, varav några kräver att frekvenshoppande spridningsspektrum, med kort uppehållstid per kanal, används. För att en användarenhet ska kunna ansluta till en basstation måste den slutföra synkronisingsfasen inom uppehållstiden, så att basstationens hoppmönster kan avkodas. På grund utav den stora signalförsvagningen, den smala bandbredden och användarenhetens egenskaper är det en stor utmaning att förkorta synkroniseringstiden. Detta examensarbete studerar olika metoder för att förkorta synkroniseringstiden i NB-IoT utan att öka kraven på användarenheten. Arbetet visar att artificiell snabb-fädning kan kombineras med tätare referenssignalering för att uppnå förbättringar i synkroniseringsprocessen som är tillräckliga för att möjliggöra operation av NB-IoT i olicensierade frekvensband.

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.

No description available.