Minimum-Energy Bandlimited Time-Variant Channel Prediction with Dynamic Subspace Selection

In current cellular communication systems the time-selective fading process is highly oversampled. We exploit this fact for time-variant flat-fading channel prediction by using dynamically selected predefined low dimensional subspaces spanned by discrete prolate spheroidal (DPS) sequences. The DPS sequences in each subspace exhibit a subspace-specific bandwidth matched to a certain Doppler frequency range. Additionally, DPS sequences are most energy concentrated in a time interval matched to the channel observation interval. Both properties enable the application of DPS sequences for minimum-energy (ME) bandlimited prediction. The dimensions of the predefined subspaces are in the range from one to five for practical communication systems. The subspace used for ME bandlimited prediction is selected based on a probabilistic bound on the reconstruction error. By contrast, time-variant channel prediction based on non-orthogonal complex exponential basis functions needs Doppler frequency estimates for each propagation path which requires high computational complexity. We compare the performance of this technique under the assumption of perfectly known complex exponentials with that of ME bandlimited prediction augmented with dynamic subspace selection. In particular we analyze the mean square prediction error of the two schemes versus the number of discrete propagation paths

Channel Prediction for Mobile MIMO Wireless Communication Systems

Temporal variation and frequency selectivity of wireless channels constitute a major drawback to the attainment of high gains in capacity and reliability offered by multiple antennas at the transmitter and receiver of a mobile communication system. Limited feedback and adaptive transmission schemes such as adaptive modulation and coding, antenna selection, power allocation and scheduling have the potential to provide the platform of attaining the high transmission rate, capacity and QoS requirements in current and future wireless communication systems. Theses schemes require both the transmitter and receiver to have accurate knowledge of Channel State Information (CSI). In Time Division Duplex (TDD) systems, CSI at the transmitter can be obtained using channel reciprocity. In Frequency Division Duplex (FDD) systems, however, CSI is typically estimated at the receiver and fed back to the transmitter via a low-rate feedback link. Due to the inherent time delays in estimation, processing and feedback, the CSI obtained from the receiver may become outdated before its actual usage at the transmitter. This results in significant performance loss, especially in high mobility environments. There is therefore a need to extrapolate the varying channel into the future, far enough to account for the delay and mitigate the performance degradation. The research in this thesis investigates parametric modeling and prediction of mobile MIMO channels for both narrowband and wideband systems. The focus is on schemes that utilize the additional spatial information offered by multiple sampling of the wave-field in multi-antenna systems to aid channel prediction. The research has led to the development of several algorithms which can be used for long range extrapolation of time-varyingchannels. Based on spatial channel modeling approaches, simple and efficient methods for the extrapolation of narrowband MIMO channels are proposed. Various extensions were also developed. These include methods for wideband channels, transmission using polarized antenna arrays, and mobile-to-mobile systems. Performance bounds on the estimation and prediction error are vital when evaluating channel estimation and prediction schemes. For this purpose, analytical expressions for bound on the estimation and prediction of polarized and non-polarized MIMO channels are derived. Using the vector formulation of the Cramer Rao bound for function of parameters, readily interpretable closed-form expressions for the prediction error bounds were found for cases with Uniform Linear Array (ULA) and Uniform Planar Array (UPA). The derived performance bounds are very simple and so provide insight into system design. The performance of the proposed algorithms was evaluated using standardized channel models. The effects of the temporal variation of multipath parameters on prediction is studied and methods for jointly tracking the channel parameters are developed. The algorithms presented can be utilized to enhance the performance of limited feedback and adaptive MIMO transmission schemes

Quelques Aspects des Réseaux Multi-Cellules Multi-Utilisateurs MIMO : Délai, Conception d'Emetteur-Récepteur, Sélection d'Utilisateurs et Topologie

In order to meet ever-growing needs for capacity in wireless networks, transmission techniques and the system models used to study their performances have rapidly evolved. From single-user single-antenna point-to-point communications to modern multi-cell multi-antenna cellular networks there have been large advances in technology. Along the way, several assumptions are made in order to have either more realistic models, but also to allow simpler analysis. We analyze three aspects of actual networks and try to benefit from them when possible or conversely, to mitigate their negative impact. This sometimes corrects overly optimistic results, for instance when delay in the channel state information (CSI) acquisition is no longer neglected. However, this sometimes also corrects overly pessimistic results, for instance when in a broadcast channel (BC) the number of users is no longer limited to be equal to the number of transmit antennas or when partial connectivity is taken into account in cellular networks.We first focus on the delay in the CSI acquisition because it greatly impairs the channel multiplexing gain if nothing is done to use the dead time during which the transmitters are not transmitting and do not yet have the CSI. We review and propose different schemes to use this dead time to improve the multiplexing gain in both the BC and the interference channel (IC). We evaluate the more relevant net multiplexing gain, taking into account the training and feedback overheads. Results are surprising because potential schemes to fight delay reveal to be burdened by impractical overheads in the BC. In the IC, an optimal scheme is proposed. It allows avoiding any loss of multiplexing gain even for significant feedback delay. Concerning the number of users, we propose a new criterion for the greedy user selection in a BC to benefit of the multi-user diversity, and two interference alignment schemes for the IC to benefit of having multiple users in each cell. Finally, partially connected cellular networks are considered and schemes to benefit from said partial connectivity to increase the multiplexing gain are proposed.Afin de répondre au besoin sans cesse croissant de capacité dans les réseaux sans fil, les techniques de transmission, et les modèles utilisés pour les étudier, ont évolués rapidement. De simples communications point à point avec une seuleantenne nous sommes passé aux réseaux cellulaires de nos jours: de multiples cellules et de multiples antennes à l’émission et à la réception. Progressivement, plusieurs hypothèses ont été faites, soit afin d’avoir des modèles réalistes, mais aussi parfois pour permettre une analyse plus simple. Nous examinons et analysons l’impact de trois aspects des réseaux réels. Cela revient parfois à corriger des résultats trop optimistes, par exemple lorsque le délai dans l’acquisition des coefficients des canaux n’est plus négligé. Cela revient parfois à corriger des résultats trop pessimistes, par exemple, lorsque dans un canal de diffusion (BC) le nombre d’utilisateurs n’est plus limité au nombre d’antennes d’émission ou lorsque la connectivité partielle est prise en compte dans les réseaux cellulaires. Plus précisément, dans cette thèse, nous nous concentrons sur le délai dans l’acquisition des coefficients des canaux par l’émetteur puisque sa prise en comptedétériore grandement le gain de multiplexage du canal si rien n’est fait pour utiliser efficacement le temps mort au cours duquel les émetteurs ne transmettent pas et n’ont pas encore la connaissance du canal. Nous examinons et proposons des schémas de transmission pour utiliser efficacement ce temps mort afin d’améliorer le gain de multiplexage. Nous évaluons le gain de multiplexage net, plus pertinent, en tenant compte le temps passé à envoyer symboles d’apprentissage et à les renvoyer aux transmetteurs. Les résultats sont surprenant puisque les schémas contre le retard de connaissance de canal se révèle être impraticables à cause du cout du partage de la connaissance des canaux. Dans les réseaux multi-cellulaires, un schéma de transmission optimal est proposé et permet de n’avoir aucune perte de gain de multiplexage même en cas de retard important dans la connaissance de canal. En ce qui concerne le nombre d’utilisateurs, nous proposons un nouveau critère pour la sélection des utilisateurs de les configurations à une seule cellule afin de bénéficier de la diversité multi-utilisateurs, et nous proposons deux schémas d’alignement d’interférence pour systèmes multi-cellulaires afin de bénéficier du fait qu’il y a généralement plusieurs utilisateurs dans chaque cellule. Enfin, les réseaux cellulaires partiellement connectés sont étudiés et des schémas bénéficiant de la connectivité partielle pour augmenter le gain de multiplexage sont proposés

A unified approach to sparse signal processing

A unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited. For each of these fields, various algorithms and techniques, which have been developed to leverage sparsity, are described succinctly. The common potential benefits of significant reduction in sampling rate and processing manipulations through sparse signal processing are revealed. The key application domains of sparse signal processing are sampling, coding, spectral estimation, array processing, compo-nent analysis, and multipath channel estimation. In terms of the sampling process and reconstruction algorithms, linkages are made with random sampling, compressed sensing and rate of innovation. The redundancy introduced by channel coding i

Low-Complexity Algorithms for Channel Estimation in Optimised Pilot-Assisted Wireless OFDM Systems

Orthogonal frequency division multiplexing (OFDM) has recently become a dominant transmission technology considered for the next generation fixed and mobile broadband wireless communication systems. OFDM has an advantage of lessening the severe effects of the frequency-selective (multipath) fading due to the band splitting into relatively flat fading subchannels, and allows for low-complexity transceiver implementation based on the fast Fourier transform algorithms. Combining OFDM modulation with multilevel frequency-domain symbol mapping (e.g., QAM) and spatial multiplexing (SM) over the multiple-input multiple-output (MIMO) channels, can theoretically achieve near Shannon capacity of the communication link. However, the high-rate and spectrumefficient system implementation requires coherent detection at the receiving end that is possible only when accurate channel state information (CSI) is available. Since in practice, the response of the wireless channel is unknown and is subject to random variation with time, the receiver typically employs a channel estimator for CSI acquisition. The channel response information retrieved by the estimator is then used by the data detector and can also be fed back to the transmitter by means of in-band or out-of-band signalling, so the latter could adapt power loading, modulation and coding parameters according to the channel conditions. Thus, design of an accurate and robust channel estimator is a crucial requirement for reliable communication through the channel, which is selective in time and frequency. In a MIMO configuration, a separate channel estimator has to be associated with each transmit/receive antenna pair, making the estimation algorithm complexity a primary concern. Pilot-assisted methods, relying on the insertion of reference symbols in certain frequencies and time slots, have been found attractive for identification of the doubly-selective radio channels from both the complexity and performance standpoint. In this dissertation, a family of the reduced-complexity estimators for the single and multiple-antenna OFDM systems is developed. The estimators are based on the transform-domain processing and have the same order of computational complexity, irrespective of the number of pilot subcarriers and their positioning. The common estimator structure represents a cascade of successive small-dimension filtering modules. The number of modules, as well as their order inside the cascade, is determined by the class of the estimator (one or two-dimensional) and availability of the channel statistics (correlation and signal-to-noise power ratio). For fine precision estimation in the multipath channels with statistics not known a priori, we propose recursive design of the filtering modules. Simulation results show that in the steady state, performance of the recursive estimators approaches that of their theoretical counterparts, which are optimal in the minimum mean square error (MMSE) sense. In contrast to the majority of the channel estimators developed so far, our modular-type architectures are suitable for the reconfigurable OFDM transceivers where the actual channel conditions influence the decision of what class of filtering algorithm to use, and how to allot pilot subcarrier positions in the band. In the pilot-assisted transmissions, channel estimation and detection are performed separately from each other over the distinct subcarrier sets. The estimator output is used only to construct the detector transform, but not as the detector input. Since performance of both channel estimation and detection depends on the signal-to-noise power vi ratio (SNR) at the corresponding subcarriers, there is a dilemma of the optimal power allocation between the data and the pilot symbols as these are conflicting requirements under the total transmit power constraint. The problem is exacerbated by the variety of channel estimators. Each kind of estimation algorithm is characterised by its own SNR gain, which in general can vary depending on the channel correlation. In this dissertation, we optimise pilot-data power allocation for the case of developed low-complexity one and two-dimensional MMSE channel estimators. The resultant contribution is manifested by the closed-form analytical expressions of the upper bound (suboptimal approximate value) on the optimal pilot-to-data power ratio (PDR) as a function of a number of design parameters (number of subcarriers, number of pilots, number of transmit antennas, effective order of the channel model, maximum Doppler shift, SNR, etc.). The resultant PDR equations can be applied to the MIMO-OFDM systems with arbitrary arrangement of the pilot subcarriers, operating in an arbitrary multipath fading channel. These properties and relatively simple functional representation of the derived analytical PDR expressions are designated to alleviate the challenging task of on-the-fly optimisation of the adaptive SM-MIMO-OFDM system, which is capable of adjusting transmit signal configuration (e.g., block length, number of pilot subcarriers or antennas) according to the established channel conditions

FMCW Signals for Radar Imaging and Channel Sounding

A linear / stepped frequency modulated continuous wave (FMCW) signal has for a long time been used in radar and channel sounding. A novel FMCW waveform known as “Gated FMCW” signal is proposed in this thesis for the suppression of strong undesired signals in microwave radar applications, such as: through-the-wall, ground penetrating, and medical imaging radar. In these applications the crosstalk signal between antennas and the reflections form the early interface (wall, ground surface, or skin respectively) are much stronger in magnitude compared to the backscattered signal from the target. Consequently, if not suppressed they overshadow the target’s return making detection a difficult task. Moreover, these strong unwanted reflections limit the radar’s dynamic range and might saturate or block the receiver causing the reflection from actual targets (especially targets with low radar cross section) to appear as noise. The effectiveness of the proposed waveform as a suppression technique was investigated in various radar scenarios, through numerical simulations and experiments. Comparisons of the radar images obtained for the radar system operating with the standard linear FMCW signal and with the proposed Gated FMCW waveform are also made. In addition to the radar work the application of FMCW signals to radio propagation measurements and channel characterisation in the 60 GHz and 2-6 GHz frequency bands in indoor and outdoor environments is described. The data are used to predict the bit error rate performance of the in-house built measurement based channel simulator and the results are compared with the theoretical multipath channel simulator available in Matlab