Dans ces travaux de thèse, nous proposons de nouvelles méthodes d’estimation de canal pour un système full-duplex dédié aux communications véhiculaires. Les deux canaux relatifs au signal utile (SOI) et au signal interférant (SI) sont estimés. Les méthodes que nous proposons sont classées selon si les pilotes des deux signaux sont envoyés séparément ou simultanément. Dans le cas de la transmission séparée des pilotes, nous proposons un algorithme se basant sur un positionnement dynamique des pilotes ainsi qu’une méthode hybride qui combine l’approche du changement de position des pilotes avec l’emploi des séquences d’apprentissage en début de trame. Nous proposons également une méthode visant à optimiser l’estimation classique qui se base sur un séquence d’apprentissage en amélioration l’estimation au niveau de chaque symbole préambule. Dans le contexte d’une transmission simultanée des pilotes, nous proposons deux algorithmes visant à améliorer les performances d’estimation par rapport aux méthodes existantes. Dans la première méthode proposée, les deux canaux SI et SOI sont estimés dans le domaine fréquentiel à l’aide des itérations de Landweber. La seconde proposition consiste à utiliser une matrice de projectionafin d’éviter le bruit engendré par les données inconnues du signal SOI lors de l’estimation. Finalement, nous proposons une méthode d’estimation de canal sélectif en temps et en fréquence pour des fréquences doppler faibles à modérées. Certaines méthodes proposées sont implémentées dans un système full-duplex expérimental qui a recours aux antennes reconfigurables pour réaliser l’annulation passive. / In this work of thesis, we propose new channel estimation approaches for a full-duplex system dédicated to vehicular communications. Both the self-interference (SI) and intended (SOI) channel are estimated. We propose different estimation méthods according to whether the pilots of the signals are transmitted jointly or separately. In the separate transmission, an estimation based on a new pilot configuration is proposed as well as a hybrid method which use both pilot configuration and training sequences.We also propose an optimisation of the conventional training-based method.It consists of improving the estimation of each training symbole. In the joint transmission, we propose two algorithms that aims to improve the estimation performances compared to the existing methods. In the first proposed method, the two channels are first estimated in the frequency domain using the Landweber iterations. The second proposition consists of using a projection matrix to manipulate only the pilots and avoid the noise that is caused by the SOI unknown datas. Finally, we propose a time and frequency-selective channel estimation for low and medium doppler frequency. Some of the proposed estimators are implemented on a real Full Duplex communication system which use Multi-reconfigurable antennas to perform the passive cancellation.

With the wide spread of wireless technology, the time for 4G has arrived, and 5G will appear not so far in the future. However, no matter whether it is 4G or 5G, low latency is a mandatory requirement for baseband processing at base stations for modern cellular standards. In particular, in a future 5G wireless system, with massive MIMO and ultra-dense cells, the demand for low round trip latency between the mobile device and the base station requires a baseband processing delay of 1 ms. This is 10 percentage of today’s LTE-A round trip latency, while at the same time massive MIMO requires large-scale matrix computations. This is especially true for channel estimation and MIMO detection at the base station. Therefore, it is essential to ensure low latency for the user data traffic. In this master’s thesis, LTE/LTE-A uplink physical layer processing is examined, especially the process of channel estimation and MIMO detection. In order to analyze this processing we compare two conventional algorithms’ performance and complexity for channel estimation and MIMO detection. The key aspect which affects the algorithms’ speed is identified as the need for “massive complex matrix inversion”. A parallel coding scheme is proposed to implement a matrix inversion kernel algorithm on a single instruction multiple data stream (SIMD) vector processor. The major contribution of this thesis is implementation and evaluation of a parallel massive complex matrix inversion algorithm. Two aspects have been addressed: the selection of the algorithm to perform this matrix computation and the implementation of a highly parallel version of this algorithm. / Med den breda spridningen av trådlös teknik, har tiden för 4G kommit, och 5G kommer inom en överskådlig framtid. Men oavsett om det gäller 4G eller 5G, låg latens är ett obligatoriskt krav för basbandsbehandling vid basstationer för moderna mobila standarder. I synnerhet i ett framtida trådlöst 5G-system, med massiva MIMO och ultratäta celler, behövs en basbandsbehandling fördröjning på 1 ms för att klara efterfrågan på en låg rundresa latens mellan den mobila enheten och basstationen. Detta är 10 procent av dagens LTE-E rundresa latens, medan massiva MIMO samtidigt kräver storskaliga matrisberäkningar. Detta är särskilt viktigt för kanaluppskattning och MIMO-detektion vid basstationen. Därför är det viktigt att se till att det är låg latens för användardatatrafik. I detta examensarbete, skall LTE/LTE-A upplänk fysiska lagret bearbetning undersökas, och då särskilt processen för kanaluppskattning och MIMO-detektion. För att analysera denna processing jämför vi två konventionella algoritmers prestationer och komplexitet för kanaluppskattning och MIMO-detektion. Den viktigaste aspekten som påverkar algoritmernas hastighet identifieras som behovet av "massiva komplex matrisinversion". Ett parallellt kodningsschema föreslås för att implementera en "matrisinversion kernel-algoritmen" på singelinstruktion multidataström (SIMD) vektorprocessor. Det största bidraget med denna avhandling är genomförande och utvärdering av en parallell massiva komplex matrisinversion kernel-algoritmen. Två aspekter har tagits upp: valet av algoritm för att utföra denna matrisberäkning och implementationen av en högst parallell version av denna algoritm.

Orthogonal Frequency Division Multiplexing (OFDM) is well known as an efficient technology for wireless communications and is widely used in many of the current and upcoming wireless and wireline communication standards. However, it has some intrinsic drawbacks, e.g., sensitivity to the inter-carrier interference (ICI) and high peak-to-average power ratio (PAPR). Additionally, the cyclic prefix (CP) is not spectrum efficient and fails when the channel delay spread exceeds the length of CP, which will result in inter-symbol interference (ISI). In order to combat or alleviate these drawbacks various techniques have been proposed, which can be categorised into two main classes: techniques that keep the structure of OFDM and meanwhile increase the system robustness or re-organise the symbol streams on each sub-carrier, and techniques that increase the ISI/ICI immunity by adopting well designed pulse shapes and/or resorting to general system lattices. The latter class are coined as Generalised FDM (GFDM) throughout this thesis to distinguish with the former class. To enable seamless handover and efficient usage of spectrum and energy, GFDM is expected to dynamically adopt pulse shapes that are optimal in doubly (time and frequency) dispersive fading channels. This is however not an easy task as the method of optimal pulse shape adaptation is still unclear, let alone efficient implementationmethods. Besides, performance of GFDM highly depends on the channel estimation quality, which is not straightforward in GFDM systems. This thesis addresses, among many other aspects of GFDM systems, measures of the time frequency localisation (TFL) property, pulse shape adaptation strategy, performance evaluation and channel estimation.  We first provide a comparative study of state-of-the-art GFDM technologies and a brief overview of the TFL functions and parameters which will be used frequently in later analysis and discussion. A framework for GFDM pulse shape optimisation is formulated targeting at minimising the combined ISI/ICI over doubly dispersive channels. We also propose a practical adaptation strategy utilising the extended Gaussian functions (EGF) and discuss the trade-off between performance and complexity.  One realisation under the umbrella of GFDM, namely OFDM/OQAM, is intensively studied and an efficient implementation method by direct discretisation of the continuous time model has been proposed.  Besides, a theoretical framework for a novel preamble-based channel estimation method has been presented and a new preamble sequence with higher gain is identified. Under the framework, an optimal pulse shape dependent preamble structure together with a suboptimal but pulse shape independent preamble structure have been proposed and evaluated in the context of OFDM/OQAM. / QC 20101108

Recently multiple antenna systems have received significant attention from researchers as a means to improve the energy and spectral efficiency of wireless systems. Among many classes of schemes, Space-Time Block codes (STBC) and Space-Time Trellis codes (STTC) have been the subject of many investigations. Both techniques provide a means for combatting the effects of multipath fading without adding much complexity to the receiver. This is especially useful in the downlink of wireless systems. In this thesis we investigate the impact of channel estimation error on the performance of both STBC and STTC. Channel estimation is especially important to consider in multiple antenna systems since (A) for coherent systems there are more channels to estimate due to multiple antennas and (B) the decoupling of data streams relies on correct channel estimation. The latter effect is due to the intentional cross-talk introduced into STBC. / Master of Science

The ever-increasing demand for private and sensitive data transmission over wireless networks has made security a crucial concern in the current and future large-scale, dynamic, and heterogeneous wireless communication systems. To address this challenge, wireless researchers have tried hard to continuously analyze the jamming threats and come up with improved countermeausres. In this research, we have analyzed the jamming-vulnerabilities of the leading multi-carrier communication systems, Orthogonal Frequency Division Multiplexing (OFDM) and Single-Carrier Frequency Division Multiple Access (SC-FDMA). In order to lay the necessary theoretical groundwork, first we derived the analytical BER expressions for BPSK/QPSK and analytical upper and lower bounds for 16-QAM for OFDMA and SC-FDMA using Pilot Symbol Assisted Channel Estimation (PSACE) techniques in Rayleigh slow-fading channel that takes into account channel estimation error as well as pilot-jamming effect. From there we advanced to propose more novel attacks on the Cyclic Prefix (CP) of SC-FDMA. The associated countermeasures developed prove to be very effective to restore the system. We are first to consider the effect of frequency-selectivity and fading correlation of channel on the achievable rates of the legitimate system under pilot-spoofing attack. With respect to jamming mitigation techniques, our approaches are more focused on Anti-Jamming (AJ) techniques rather than Low Probability of Intercept (LPI) methods. The Channel State Information (CSI) of the two transceivers and the CSI between the jammer and the target play critical roles in ensuring the effectiveness of jamming and nulling attacks. Although current literature is rich with different channel estimation techniques between two legitimate transceivers, it does not have much to offer in the area of channel estimation from jammer's perspective. In this dissertation, we have proposed novel, computationally simple, deterministic, and optimal blind channel estimation techniques for PSK-OFDM as well as QAM-OFDM that estimate the jammer channel to the target precisely in high Signal-to-Noise (SNR) environment from a single OFDM symbol and thus perform well in mobile radio channel. We have also presented the feasibility analysis of estimating transceiver channel from jammer's perspective at the transmitter as well as receiver side of the underlying OFDM system. / Ph. D.

This thesis examines the benefits of using adaptive modulation and coding in terms of spectral efficiency and probability of bit error. Specifically, we examine the performance enhancement made possible by using linear prediction along with channel estimation in conjunction with adaptive modulation. We begin this manuscript with basic fundamentals of our study, followed by a detailed view of simulations, their results, and our conclusions from them. The study includes simulations in slow and moderately fast flat fading Rayleigh channels. We present our findings regarding the advantages of using predictive measures to foresee the state of the channel and make adjustments to transmissions accordingly. In addition to finding the general advantages of channel prediction in adaptive modulation, we explore various ways to adjust the prediction algorithm when we are faced with high Doppler rates and fast fading. By the end of this work, we should have a better understanding of when channel prediction is most valuable to adaptive modulation and when it is weakest, and how we can alleviate the problems that prediction will have in harsh environments. / Master of Science

Bayesian approaches for sparse signal recovery have enjoyed a long-standing history in signal processing and machine learning literature. Among the Bayesian techniques, the expectation maximization based Sparse Bayesian Learning(SBL) approach is an iterative procedure with global convergence guarantee to a local optimum, which uses a parameterized prior that encourages sparsity under an evidence maximization frame¬work. SBL has been successfully employed in a wide range of applications ranging from image processing to communications. In this thesis, we propose novel, efficient and low-complexity SBL-based algorithms that exploit structured sparsity in the presence of fully/partially known measurement matrices. We apply the proposed algorithms to the problem of channel estimation and data detection in Orthogonal Frequency Division Multiplexing(OFDM) systems. Further, we derive Cram´er Rao type lower Bounds(CRB) for the single and multiple measurement vector SBL problem of estimating compressible vectors and their prior distribution parameters. The main contributions of the thesis are as follows: We derive Hybrid, Bayesian and Marginalized Cram´er Rao lower bounds for the problem of estimating compressible vectors drawn from a Student-t prior distribution. We derive CRBs that encompass the deterministic or random nature of the unknown parameters of the prior distribution and the regression noise variance. We use the derived bounds to uncover the relationship between the compressibility and Mean Square Error(MSE) in the estimates. Through simulations, we demonstrate the dependence of the MSE performance of SBL based estimators on the compressibility of the vector. OFDM is a well-known multi-carrier modulation technique that provides high spectral efficiency and resilience to multi-path distortion of the wireless channel It is well-known that the impulse response of a wideband wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this thesis, we consider the estimation of the unknown channel coefficients and its support in SISO-OFDM systems using a SBL framework. We propose novel pilot-only and joint channel estimation and data detection algorithms in block-fading and time-varying scenarios. In the latter case, we use a first order auto-regressive model for the time-variations, and propose recursive, low-complexity Kalman filtering based algorithms for channel estimation. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the MSE and coded bit error rate performance. • Multiple Input Multiple Output(MIMO) combined with OFDM harnesses the inherent advantages of OFDM along with the diversity and multiplexing advantages of a MIMO system. The impulse response of wireless channels between the Nt transmit and Nr receive antennas of a MIMO-OFDM system are group approximately sparse(ga-sparse),i.e. ,the Nt Nr channels have a small number of significant paths relative to the channel delay spread, and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wire¬less channels are also group approximately-cluster sparse(ga-csparse),i.e.,every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this thesis, we cast the problem of estimating the ga-sparse and ga-csparse block-fading and time-varying channels using a multiple measurement SBL framework. We propose a bouquet of novel algorithms for MIMO-OFDM systems that generalize the algorithms proposed in the context of SISO-OFDM systems. The efficacy of the proposed techniques are demonstrated in terms of MSE and coded bit error rate performance.

[pt] A utilização das linhas de potência para fins de comunicação vem recebendo grande atenção nos últimos anos, principalmente devido a grande demanda por serviços de telecomunicações. A grande virtude é que as linhas de potência para comunicação apresentam uma solução sem a necessidade de nova fiação. Além disso, apresentam saída de potência disponível em todos os cômodos de uma residência, onde o terminal de comunicação possa ser usado, são de fácil instalação e acima de tudo apresentam custo reduzido. Sendo assim a comunicação através de linhas de potência vem se mostrando uma solução viável na oferta de serviços de telecomunicações. Esta tese investigou os sistemas PLC no que diz respeito à estimação do canal. Foi desenvolvido um método paramétrico de estimação do canal PLC baseado no algoritmo EM (Expectation Maximization). Foi feita a avaliação de desempenho combinando modulação OFDM (Orthogonal Frequency Division Multiplexing), estimação do canal PLC e equalização, sendo utilizado como referencias os equalizadores ZF (Zero Forcing) e MMSE (Minimum Mean Square Error). / [en] The powerline communications systems have been receiving increasing attention in last few years. Power line communications presents a no new wires solution with the additional advantages of ubiquitous node availability, easy installation, and cost effectiveness. This thesis investigation the powerline estimation channel. It was presented parametric channel estimation method using EM (Expectation Maximization) algorithm. The performance using OFDM (Orthogonal Frequency Division Multiplexing), PLC Channel estimation and equalization was availability. The performance was studied using two equalization techniques Zero- Forcing and Minimum Mean Square Error.

[pt] crescimento dos sistemas de comunicações móveis celulares e dos sistemas de rádio difusão de sinais de áudio e vídeo tem despertado grande interesse na pesquisa de novos métodos para a transmissão de sinais nestas redes. A necessidade de se transmitir dados em altas taxas, com significante eficiência no uso da largura de faixa de freqüências disponível, e por meio de um canal de propagação ruidoso e variante no tempo, constitui o principal problema para o desenvolvimento de novas técnicas de trasmissão de sinais. Dentro deste contexto, esta dissertação trata do uso dos conceitos de transmissão digital e filtragem adaptativa para a demodulação de sinais OFDM (Orthogonal Frequency Division Multiplexing). A equalização de sinais antes e após o estágio de DFT (Discrete Fourier Transform) no receptor e as técnicas de estimação de canal são o objeto principal de estudo deste trabalho. Os resultados dos experimentos são analisados em termos da taxa de erro de bit média obtida e da convergência dos algoritmos empregados nas etapas de equalização e estimação de canal no receptor. / [en] The growth of cellular mobile communication systems and audio and video broadcasting systems has stimulated great interest in the research of new methods for the signal transmission in these networks. The high rate data transmission, with significant efficiency in the use of the available bandwidth, in a noisy and time variant channel, constitutes the main problem for the development of new techniques for signal transmission. In this context, this dissertation deals with the use of the concepts of digital transmission and adaptive filtering for the demodulation of OFDM (Orthogonal Frequency Division Multiplexing) signals. The equalization pre and post DFT (Discrete Fourier Transform) in the receiver and the channel estimation techniques are the main object of study in this work. The results of the experiments are analyzed in terms of the mean bit error rate achieved and the convergence for the algorithms used in the stages of equalization and channel estimation in the receiver.

This dissertation develops and analyzes several techniques for improving channel estimation and tracking performance in distributed multi-input multi-output (D-MIMO) wireless communication systems. D-MIMO communication systems have been studied for the last decade and are known to offer the benefits of antenna arrays, e.g., improved range and data rates, to systems of single-antenna devices. D-MIMO communication systems are considered a promising technology for future wireless standards including advanced cellular communication systems. This dissertation considers problems related to channel estimation and tracking in D-MIMO communication systems and is focused on three related topics: (i) characterizing oscillator stability for nodes in D-MIMO systems, (ii) the development of an optimal unified tracking framework and a performance comparison to previously considered sub-optimal tracking approaches, and (iii) incorporating independent kinematics into dynamic channel models and using accelerometers to improve channel tracking performance. A key challenge of D-MIMO systems is estimating and tracking the time-varying channels present between each pair of nodes in the system. Even if the propagation channel between a pair of nodes is time-invariant, the independent local oscillators in each node cause the carrier phases and frequencies and the effective channels between the nodes to have random time-varying phase offsets. The first part of this dissertation considers the problem of characterizing the stability parameters of the oscillators used as references for the transmitted waveforms. Having good estimates of these parameters is critical to facilitate optimal tracking of the phase and frequency offsets. We develop a new method for estimating these oscillator stability parameters based on Allan deviation measurements and compare this method to several previously developed parameter estimation techniques based on innovation covariance whitening. The Allan deviation method is validated with both simulations and experimental data from low-precision and high-precision oscillators. The second part of this dissertation considers a D-MIMO scenario with $N_t$ transmitters and $N_r$ receivers. While there are $N_t imes N_r$ node-to-node pairwise channels in such a system, there are only $N_t + N_r$ independent oscillators. We develop a new unified tracking model where one Kalman filter jointly tracks all of the pairwise channels and compare the performance of unified tracking to previously developed suboptimal local tracking approaches where the channels are not jointly tracked. Numerical results show that unified tracking tends to provide similar beamforming performance to local tracking but can provide significantly better nullforming performance in some scenarios. The third part of this dissertation considers a scenario where the transmit nodes in a D-MIMO system have independent kinematics. In general, this makes the channel tracking problem more difficult since the independent kinematics make the D-MIMO channels less predictable. We develop dynamics models which incorporate the effects of acceleration on oscillator frequency and displacement on propagation time. The tracking performance of a system with conventional feedback is compared to a system with conventional feedback and local accelerometer measurements. Numerical results show that the tracking performance is significantly improved with local accelerometer measurements.