Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems

Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.

Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201

Reduced Complexity Sequential Monte Carlo Algorithms for Blind Receivers

Monte Carlo algorithms can be used to estimate the state of a system given relative observations. In this dissertation, these algorithms are applied to physical layer communications system models to estimate channel state information, to obtain soft information about transmitted symbols or multiple access interference, or to obtain estimates of all of these by joint estimation. Initially, we develop and analyze a multiple access technique utilizing mutually orthogonal complementary sets (MOCS) of sequences. These codes deliberately introduce inter-chip interference, which is naturally eliminated during processing at the receiver. However, channel impairments can destroy their orthogonality properties and additional processing becomes necessary. We utilize Monte Carlo algorithms to perform joint channel and symbol estimation for systems utilizing MOCS sequences as spreading codes. We apply Rao-Blackwellization to reduce the required number of particles. However, dense signaling constellations, multiuser environments, and the interchannel interference introduced by the spreading codes all increase the dimensionality of the symbol state space significantly. A full maximum likelihood solution is computationally expensive and generally not practical. However, obtaining the optimum solution is critical, and looking at only a part of the symbol space is generally not a good solution. We have sought algorithms that would guarantee that the correct transmitted symbol is considered, while only sampling a portion of the full symbol space. The performance of the proposed method is comparable to the Maximum Likelihood (ML) algorithm. While the computational complexity of ML increases exponentially with the dimensionality of the problem, the complexity of our approach increases only quadratically. Markovian structures such as the one imposed by MOCS spreading sequences can be seen in other physical layer structures as well. We have applied this partitioning approach with some modification to blind equalization of frequency selective fading channel and to multiple-input multiple output receivers that track channel changes. Additionally, we develop a method that obtains a metric for quantifying the convergence rate of Monte Carlo algorithms. Our approach yields an eigenvalue based method that is useful in identifying sources of slow convergence and estimation inaccuracy.Ph.D.Committee Chair: Douglas B. Williams; Committee Member: Brani Vidakovic; Committee Member: G. Tong zhou; Committee Member: Gordon Stuber; Committee Member: James H. McClella

Traitement du signal pour les communications numériques au travers de canaux radio-mobiles

This manuscript of ''Habilitation à diriger les Recherches'' (Habilitation to conduct researches) gives me the opportunity to take stock of the last 14 years on my associate professor activities and on my research works in the field of signal processing for digital communications, particularly for radio-mobile communications. The purpose of this signal processing is generally to obtain a robust transmission, despite the passage of digital information through a communication channel disrupted by the mobility between the transmitter and the receiver (Doppler effect), the phenomenon of echoes (multi-path propagation), the addition of noise or interference, or by limitations in bandwidth, in transmitted power or in signal-to-noise ratio. In order to recover properly the digital information, the receiver needs in general to have an accurate knowledge of the channel state. Much of my work has focused on receiver synchronization or more generally on the dynamic estimation of the channel parameters (delays, phases, amplitudes, Doppler shifts, ...). We have developed estimators and studied their performance in asymptotic variance, and have compared them to minimum lower bound (Cramer-rao or Bayesian Cramer Rao bounds). Some other studies have focused only on the recovering of information (''detection'' or ''equalization'' task) by the receiver after channel estimation, or proposed and analyzed emission / reception schemes, reliable for certain scenarios (transmit diversity scheme for flat fading channel, scheme with high energy efficiency, ...).Ce mémoire de HDR est l'occasion de dresser un bilan des 14 dernières années concernant mes activités d'enseignant-chercheur et mes travaux de recherche dans le domaine du traitement du signal pour les communications numériques, et plus particulièrement les communications radio-mobiles. L'objet de ce traitement du signal est globalement l'obtention d'une transmission robuste, malgré le passage de l'information numérique au travers d'un canal de communication perturbé par la mobilité entre l'émetteur et le récepteur (effet Doppler), le phénomène d'échos, l'addition de bruit ou d'interférence, ou encore par des limitations en bande-passante, en puissance transmise ou en rapport-signal à bruit. Afin de restituer au mieux l'information numérique, le récepteur a en général besoin de disposer d'une connaissance précise du canal. Une grande partie de mes travaux s'est intéressé à l'estimation dynamique des paramètres de ce canal (retards, phases, amplitudes, décalages Doppler, ...), et en particulier à la synchronisation du récepteur. Quelques autres travaux se sont intéressés seulement à la restitution de l'information (tâches de ''détection'' ou d' ''égalisation'') par le récepteur une fois le canal estimé, ou à des schémas d'émission / réception spécifiques. La synthèse des travaux commence par une introduction générale décrivant les ''canaux de communications'' et leurs problèmes potentiels, et positionne chacun de mes travaux en ces termes. Une première partie s'intéresse aux techniques de réception pour les signaux à spectre étalé des systèmes d'accès multiple à répartition par codes (CDMA). Ces systèmes large-bande offrent un fort pouvoir de résolution temporelle et des degrés de liberté, que nous avons exploités pour étudier l'égalisation et la synchronisation (de retard et de phase) en présence de trajets multiples et d'utilisateurs multiples. La première partie regroupe aussi d'autres schémas d'émission/réception, proposés pour leur robustesse dans différents scénarios (schéma à diversité pour canaux à évanouissement plats, schéma à forte efficacité énergétique, ...). La seconde partie est consacrée à l'estimation dynamique Bayésienne des paramètres du canal. On suppose ici qu'une partie des paramètres à estimer exhibe des variations temporelles aléatoires selon une certaine loi à priori. Nous proposons d'abord des estimateurs et des bornes minimales d'estimation pour des modèles de transmission relativement complexes, en raison de la distorsion temporelle due à la forte mobilité en modulation multi-porteuse (OFDM), ou de la présence de plusieurs paramètres à estimer conjointement, ou encore de non linéarités dans les modèles. Nous nous focalisons ensuite sur le problème d'estimation des amplitudes complexes des trajets d'un canal à évolution lente (à 1 ou plusieurs bonds). Nous proposons des estimateurs récursifs (dénommés CATL, pour ''Complex Amplitude Tracking Loop'') à structure imposée inspirée par les boucles à verrouillage de phase numériques, de performance asymptotiques proches des bornes minimales. Les formules analytiques approchées de performances asymptotiques et de réglages de ces estimateurs sont établies sous forme de simples fonctions des paramètres physiques (spectre Doppler, retards, niveau de bruit). Puis étant donné les liens établis entre ces estimateurs CATL et certains filtres de Kalman (construits pour des modèles d'état de type marche aléatoire intégrée), les formules approchées de performances asymptotiques et de réglage de ces filtres de Kalman sont aussi dérivées

Journal of Telecommunications and Information Technology, 2006, nr 1

kwartalni