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.

Equalization Techniques of Control and Non-Payload Communication Links for Unmanned Aerial Vehicles

In the next years, several new applications involving unmanned aerial vehicles (UAVs) for public and commercial uses are envisaged. In such developments, since UAVs are expected to operate within the public airspace, a key issue is the design of reliable control and non-payload communication (CNPC) links connecting the ground control station to the UAV. At the physical layer, CNPC design must cope with time- and frequency-selectivity (so-called double selectivity) of the wireless channel, due to lowaltitude operation and flight dynamics of the UAV. In this paper, we consider the transmission of continuous phase modulated (CPM) signals for UAV CNPC links operating over doubly-selective channels. Leveraging on the Laurent representation for a CPM signal, we design a two-stage receiver: the first one is a linear time-varying (LTV) equalizer, synthesized under either the zero-forcing (ZF) or minimum mean-square error (MMSE) criterion; the second one recovers the transmitted symbols from the pseudo-symbols of the Laurent representation in a simple recursive manner. In addition to LTV-ZF and LTV-MMSE equalizers, their widely-linear versions are also developed, to take into account the possible noncircular features of the CPM signal. Moreover, relying on a basis expansion model (BEM) of the doubly-selective channel, we derive frequency-shift versions of the proposed equalizers, by discussing their complexity issues and proposing simplified implementations. Monte Carlo numerical simulations show that the proposed receiving structures are able to satisfactorily equalize the doubly-selective channel in typical UAV scenarios

Timing and Frequency Synchronization and Channel Estimation in OFDM-based Systems

Orthogonal frequency division multiplexing (OFDM) due to its appealing features, such as robustness against frequency selective fading and simple channel equalization, is adopted in communications systems such as WLAN, WiMAX and DVB. However, OFDM systems are sensitive to synchronization errors caused by timing and frequency offsets. Besides, the OFDM receiver has to perform channel estimation for coherent detection. The goal of this thesis is to investigate new methods for timing and frequency synchronization and channel estimation in OFDM-based systems. First, we investigate new methods for preamble-aided coarse timing estimation in OFDM systems. Two novel timing metrics using high order statistics-based correlation and differential normalization functions are proposed. The performance of the new timing metrics is evaluated using different criteria including class-separability, robustness to the carrier frequency offset, and computational complexity. It is shown that the new timing metrics can considerably increase the class-separability due to their more distinct values at correct and wrong timing instants, and thus give a significantly better detection performance than the existing timing metrics do. Furthermore, a new method for coarse estimation of the start of the frame is proposed, which remarkably reduces the probability of inter-symbol interference (ISI). The improved performances of the new schemes in multipath fading channels are shown by the probabilities of false alarm, missed-detection and ISI obtained through computer simulations. Second, a novel pilot-aided algorithm is proposed for the detection of integer frequency offset (IFO) in OFDM systems. By transforming the IFO into two new integer parameters, the proposed method can largely reduce the number of trial values for the true IFO. The two new integer parameters are detected using two different pilot sequences, a periodic pilot sequence and an aperiodic pilot sequence. It is shown that the new scheme can significantly reduce the computational complexity while achieving almost the same performance as the previous methods do. Third, we propose a method for joint timing and frequency synchronization and channel estimation for OFDM systems that operate in doubly selective channels. Basis expansion modeling (BEM) that captures the time variations of the channel is used to reduce the number of unknown channel parameters. The BEM coefficients along with the timing and frequency offsets are estimated by using a maximum likelihood (ML) approach. An efficient algorithm is then proposed for reducing the computational complexity of the joint estimation. The complexity of the new method is assessed in terms of the number of multiplications. The mean square estimation error of the proposed method is evaluated in comparison with previous methods, indicating a remarkable performance improvement by the new method. Fourth, we present a new scheme for joint estimation of CFO and doubly selective channel in orthogonal frequency division multiplexing systems. In the proposed preamble-aided method, the time-varying channel is represented using BEM. CFO and BEM coefficients are estimated using the principles of particle and Kalman filtering. The performance of the new method in multipath time-varying channels is investigated in comparison with previous schemes. The simulation results indicate a remarkable performance improvement in terms of the mean square errors of CFO and channel estimates. Fifth, a novel algorithm is proposed for timing and frequency synchronization and channel estimation in the uplink of orthogonal frequency division multiple access (OFDMA) systems by considering high-mobility situations and the generalized subcarrier assignment. By using BEM to represent a doubly selective channel, a maximum likelihood (ML) approach is proposed to jointly estimate the timing and frequency offsets of different users as well as the BEM coefficients of the time-varying channels. A space-alternating generalized expectation-maximization algorithm is then employed to transform the maximization problem for all users into several simpler maximization problems for each user. The computational complexity of the new timing and frequency offset estimator is analyzed and its performance in comparison with that of existing methods using the mean square error is evaluated . Finally, two novel approaches for joint CFO and doubly selective channel estimation in the uplink of multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) systems are presented. Considering high-mobility situations, where channels change within an OFDMA symbol interval, and the time varying nature of CFOs, BEM is employed to represent the time variations of the channel. Two new approaches are then proposed based on Schmidt Kalman filtering (SKF). The first approach utilizes Schmidt extended Kalman filtering for each user to estimate the CFO and BEM coefficients. The second approach uses Gaussian particle filter along with SKF to estimate the CFO and BEM coefficients of each user. The Bayesian Cramer Rao bound is derived, and performance of the new schemes are evaluated using mean square error. It is demonstrated that the new schemes can significantly improve the mean square error performance in comparison with that of the existing methods

Turbo Detection in Rayleigh flat fading channel with unknown statistics

ABSTRACT The turbo detection of turbo coded symbols over correlated Rayleigh flat fading channels generated according to Jakes' model is considered in this paper. We propose a method to estimate the channel signal-to-noise ratio (SNR) and the maximum Doppler frequency. These statistics are required by the linear minimum mean squared error (LMMSE) channel estimator. To improve the system convergence, we redefine the channel reliability factor by taking into account the channel estimation error statistics. Simulation results for rate 1/3 turbo code and two different normalized fading rates show that the use of the new reliability factor greatly improves the performance. The improvement is more substantial when channel statistics are unknown. K EYWORDS MAP-BCJR decoder, SNR, maximum Doppler frequency, turbo processing, channel reliability

Transmission strategies for broadband wireless systems with MMSE turbo equalization

This monograph details efficient transmission strategies for single-carrier wireless broadband communication systems employing iterative (turbo) equalization. In particular, the first part focuses on the design and analysis of low complexity and robust MMSE-based turbo equalizers operating in the frequency domain. Accordingly, several novel receiver schemes are presented which improve the convergence properties and error performance over the existing turbo equalizers. The second part discusses concepts and algorithms that aim to increase the power and spectral efficiency of the communication system by efficiently exploiting the available resources at the transmitter side based upon the channel conditions. The challenging issue encountered in this context is how the transmission rate and power can be optimized, while a specific convergence constraint of the turbo equalizer is guaranteed.Die vorliegende Arbeit beschäftigt sich mit dem Entwurf und der Analyse von effizienten Übertragungs-konzepten für drahtlose, breitbandige Einträger-Kommunikationssysteme mit iterativer (Turbo-) Entzerrung und Kanaldekodierung. Dies beinhaltet einerseits die Entwicklung von empfängerseitigen Frequenzbereichs-entzerrern mit geringer Komplexität basierend auf dem Prinzip der Soft Interference Cancellation Minimum-Mean Squared-Error (SC-MMSE) Filterung und andererseits den Entwurf von senderseitigen Algorithmen, die durch Ausnutzung von Kanalzustandsinformationen die Bandbreiten- und Leistungseffizienz in Ein- und Mehrnutzersystemen mit Mehrfachantennen (sog. Multiple-Input Multiple-Output (MIMO)) verbessern. Im ersten Teil dieser Arbeit wird ein allgemeiner Ansatz für Verfahren zur Turbo-Entzerrung nach dem Prinzip der linearen MMSE-Schätzung, der nichtlinearen MMSE-Schätzung sowie der kombinierten MMSE- und Maximum-a-Posteriori (MAP)-Schätzung vorgestellt. In diesem Zusammenhang werden zwei neue Empfängerkonzepte, die eine Steigerung der Leistungsfähigkeit und Verbesserung der Konvergenz in Bezug auf existierende SC-MMSE Turbo-Entzerrer in verschiedenen Kanalumgebungen erzielen, eingeführt. Der erste Empfänger - PDA SC-MMSE - stellt eine Kombination aus dem Probabilistic-Data-Association (PDA) Ansatz und dem bekannten SC-MMSE Entzerrer dar. Im Gegensatz zum SC-MMSE nutzt der PDA SC-MMSE eine interne Entscheidungsrückführung, so dass zur Unterdrückung von Interferenzen neben den a priori Informationen der Kanaldekodierung auch weiche Entscheidungen der vorherigen Detektions-schritte berücksichtigt werden. Durch die zusätzlich interne Entscheidungsrückführung erzielt der PDA SC-MMSE einen wesentlichen Gewinn an Performance in räumlich unkorrelierten MIMO-Kanälen gegenüber dem SC-MMSE, ohne dabei die Komplexität des Entzerrers wesentlich zu erhöhen. Der zweite Empfänger - hybrid SC-MMSE - bildet eine Verknüpfung von gruppenbasierter SC-MMSE Frequenzbereichsfilterung und MAP-Detektion. Dieser Empfänger besitzt eine skalierbare Berechnungskomplexität und weist eine hohe Robustheit gegenüber räumlichen Korrelationen in MIMO-Kanälen auf. Die numerischen Ergebnisse von Simulationen basierend auf Messungen mit einem Channel-Sounder in Mehrnutzerkanälen mit starken räumlichen Korrelationen zeigen eindrucksvoll die Überlegenheit des hybriden SC-MMSE-Ansatzes gegenüber dem konventionellen SC-MMSE-basiertem Empfänger. Im zweiten Teil wird der Einfluss von System- und Kanalmodellparametern auf die Konvergenzeigenschaften der vorgestellten iterativen Empfänger mit Hilfe sogenannter Korrelationsdiagramme untersucht. Durch semi-analytische Berechnungen der Entzerrer- und Kanaldecoder-Korrelationsfunktionen wird eine einfache Berechnungsvorschrift zur Vorhersage der Bitfehlerwahrscheinlichkeit von SC-MMSE und PDA SC-MMSE Turbo Entzerrern für MIMO-Fadingkanäle entwickelt. Des Weiteren werden zwei Fehlerschranken für die Ausfallwahrscheinlichkeit der Empfänger vorgestellt. Die semi-analytische Methode und die abgeleiteten Fehlerschranken ermöglichen eine aufwandsgeringe Abschätzung sowie Optimierung der Leistungsfähigkeit des iterativen Systems. Im dritten und abschließenden Teil werden Strategien zur Raten- und Leistungszuweisung in Kommunikationssystemen mit konventionellen iterativen SC-MMSE Empfängern untersucht. Zunächst wird das Problem der Maximierung der instantanen Summendatenrate unter der Berücksichtigung der Konvergenz des iterativen Empfängers für einen Zweinutzerkanal mit fester Leistungsallokation betrachtet. Mit Hilfe des Flächentheorems von Extrinsic-Information-Transfer (EXIT)-Funktionen wird eine obere Schranke für die erreichbare Ratenregion hergeleitet. Auf Grundlage dieser Schranke wird ein einfacher Algorithmus entwickelt, der für jeden Nutzer aus einer Menge von vorgegebenen Kanalcodes mit verschiedenen Codierraten denjenigen auswählt, der den instantanen Datendurchsatz des Mehrnutzersystems verbessert. Neben der instantanen Ratenzuweisung wird auch ein ausfallbasierter Ansatz zur Ratenzuweisung entwickelt. Hierbei erfolgt die Auswahl der Kanalcodes für die Nutzer unter Berücksichtigung der Einhaltung einer bestimmten Ausfallwahrscheinlichkeit (outage probability) des iterativen Empfängers. Des Weiteren wird ein neues Entwurfskriterium für irreguläre Faltungscodes hergeleitet, das die Ausfallwahrscheinlichkeit von Turbo SC-MMSE Systemen verringert und somit die Zuverlässigkeit der Datenübertragung erhöht. Eine Reihe von Simulationsergebnissen von Kapazitäts- und Durchsatzberechnungen werden vorgestellt, die die Wirksamkeit der vorgeschlagenen Algorithmen und Optimierungsverfahren in Mehrnutzerkanälen belegen. Abschließend werden außerdem verschiedene Maßnahmen zur Minimierung der Sendeleistung in Einnutzersystemen mit senderseitiger Singular-Value-Decomposition (SVD)-basierter Vorcodierung untersucht. Es wird gezeigt, dass eine Methode, welche die Leistungspegel des Senders hinsichtlich der Bitfehlerrate des iterativen Empfängers optimiert, den konventionellen Verfahren zur Leistungszuweisung überlegen ist

Advanced receivers for distributed cooperation in mobile ad hoc networks

Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato

Analysis of and techniques for adaptive equalization for underwater acoustic communication

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2011Underwater wireless communication is quickly becoming a necessity for applications in ocean science, defense, and homeland security. Acoustics remains the only practical means of accomplishing long-range communication in the ocean. The acoustic communication channel is fraught with difficulties including limited available bandwidth, long delay-spread, time-variability, and Doppler spreading. These difficulties reduce the reliability of the communication system and make high data-rate communication challenging. Adaptive decision feedback equalization is a common method to compensate for distortions introduced by the underwater acoustic channel. Limited work has been done thus far to introduce the physics of the underwater channel into improving and better understanding the operation of a decision feedback equalizer. This thesis examines how to use physical models to improve the reliability and reduce the computational complexity of the decision feedback equalizer. The specific topics covered by this work are: how to handle channel estimation errors for the time varying channel, how to use angular constraints imposed by the environment into an array receiver, what happens when there is a mismatch between the true channel order and the estimated channel order, and why there is a performance difference between the direct adaptation and channel estimation based methods for computing the equalizer coefficients. For each of these topics, algorithms are provided that help create a more robust equalizer with lower computational complexity for the underwater channel.This work would not have been possible without support from the O ce of Naval Research, through a Special Research Award in Acoustics Graduate Fellowship (ONR Grant #N00014-09-1-0540), with additional support from ONR Grant #N00014-05- 10085 and ONR Grant #N00014-07-10184