Space time transceiver design over multipath fading channels

Imperial Users onl

Advanced receiver structures for mobile MIMO multicarrier communication systems

Beyond third generation (3G) and fourth generation (4G) wireless communication systems are targeting far higher data rates, spectral efficiency and mobility requirements than existing 3G networks. By using multiple antennas at the transmitter and the receiver, multiple-input multiple-output (MIMO) technology allows improving both the spectral efficiency (bits/s/Hz), the coverage, and link reliability of the system. Multicarrier modulation such as orthogonal frequency division multiplexing (OFDM) is a powerful technique to handle impairments specific to the wireless radio channel. The combination of multicarrier modulation together with MIMO signaling provides a feasible physical layer technology for future beyond 3G and fourth generation communication systems. The theoretical benefits of MIMO and multicarrier modulation may not be fully achieved because the wireless transmission channels are time and frequency selective. Also, high data rates call for a large bandwidth and high carrier frequencies. As a result, an important Doppler spread is likely to be experienced, leading to variations of the channel over very short period of time. At the same time, transceiver front-end imperfections, mobility and rich scattering environments cause frequency synchronization errors. Unlike their single-carrier counterparts, multi-carrier transmissions are extremely sensitive to carrier frequency offsets (CFO). Therefore, reliable channel estimation and frequency synchronization are necessary to obtain the benefits of MIMO OFDM in mobile systems. These two topics are the main research problems in this thesis. An algorithm for the joint estimation and tracking of channel and CFO parameters in MIMO OFDM is developed in this thesis. A specific state-space model is introduced for MIMO OFDM systems impaired by multiple carrier frequency offsets under time-frequency selective fading. In MIMO systems, multiple frequency offsets are justified by mobility, rich scattering environment and large angle spread, as well as potentially separate radio frequency - intermediate frequency chains. An extended Kalman filter stage tracks channel and CFO parameters. Tracking takes place in time domain, which ensures reduced computational complexity, robustness to estimation errors as well as low estimation variance in comparison to frequency domain processing. The thesis also addresses the problem of blind carrier frequency synchronization in OFDM. Blind techniques exploit statistical or structural properties of the OFDM modulation. Two novel approaches are proposed for blind fine CFO estimation. The first one aims at restoring the orthogonality of the OFDM transmission by exploiting the properties of the received signal covariance matrix. The second approach is a subspace algorithm exploiting the correlation of the channel frequency response among the subcarriers. Both methods achieve reliable estimation of the CFO regardless of multipath fading. The subspace algorithm needs extremely small sample support, which is a key feature in the face of time-selective channels. Finally, the Cramér-Rao (CRB) bound is established for the problem in order to assess the large sample performance of the proposed algorithms.reviewe

Evaluation of phase-frequency instability when processing complex radar signals

A new radar system for digital signal processing before detection is proposed. These are the guidelines for selecting an intermediate frequency for signal processing. The features of signal processing in the case of echo-signal selection by the features of the correlation properties of their complex bypass are described. This paper presents the study of ambiguity function (AF) when processing complex radar signals. In this work, the AF synthesis was performed considering non-determined components and the presence of phase-frequency instability. The received result enhances the potentials for distinguishing an incoherent radar signal. The numerical simulation results of received AF are presented. Considering fluctuation components in the complex AF, depending on the laws of the distribution of amplitude and frequency fluctuations and their parameters, allowed to get the gain in the width of the main lobe from the units to tens of times. Paper represents original analytical expressions for AF of radio-signals modulated by narrow band random processes with various distribution laws

Estimation of Radio Channel Parameters

Kurzfassung Diese Dissertation behandelt die Schätzung der Modellparameter einer Momentanaufnahme des Mobilfunkkanals. Das besondere Augenmerk liegt zum einen auf der Entwicklung eines generischen Datenmodells für den gemessenen Funkkanal, welches für die hochauflösende Parameterschätzung geeignet ist. Der zweite Schwerpunkt dieser Arbeit ist die Entwicklung eines robusten Parameterschätzers für die Bestimmung der Parameter des entworfenen Modells aus Funkkanalmessdaten. Entsprechend dieser logischen Abfolge ist auch der Aufbau dieser Arbeit. Im ersten Teil wird ausgehend von einem aus der Literatur bekannten strahlenoptischen Modell eine algebraisch handhabbare Darstellung von beobachteten Wellenausbreitungspfaden entwickelt. Das mathematische Modell erlaubt die Beschreibung von SISO (single-input-single-output)- Übertragungssystemen, also von Systemen mit einer Sendeantenne und einer Empfangsantenne, als auch die Beschreibung von solchen Systemen mit mehreren Sende- und/oder Empfangsantennen. Diese Systeme werden im Allgemeinen auch als SIMO- (single-input-multiple-output), MISO- (multiple-input-single-output) oder MIMO-Systeme (multiple-input-multiple-output) bezeichnet. Im Gegensatz zu bekannten Konzepten enthält das entwickelte Modell keine Restriktionen bezüglich der modellierbaren Antennenarrayarchitekturen. Dies ist besonders wichtig in Hinblick auf die möglichst vollständige Erfassung der räumlichen Struktur des Funkkanals. Die Flexibilität des Modells ist eine Grundvoraussetzung für die optimale Anpassung der Antennenstruktur an die Messaufgabe. Eine solche angepasste Antennenarraystruktur ist zum Beispiel eine zylindrische Anordnung von Antennenelementen. Sie ist gut geeignet für die Erfassung der räumlichen Struktur des Funkkanals (Azimut und Elevation) in so genannten Outdoor- Funkszenarien. Weiterhin wird im ersten Teil eine neue Komponente des Funkkanaldatenmodells eingeführt, welche den Beitrag verteilter (diffuser) Streuungen zur Funkübertragung beschreibt. Die neue Modellkomponente spielt eine Schlüsselrolle bei der Entwicklung eines robusten Parameterschätzers im Hauptteil dieser Arbeit. Die fehlende Modellierung der verteilten Streuungen ist eine der Hauptursachen für die begrenzte Anwendbarkeit und die oft kritisierte fehlende Robustheit von hochauflösenden Funkkanalparameterschätzern, die in der Literatur etabliert sind. Das neue Datenmodell beschreibt die so genannten dominanten Ausbreitungspfade durch eine deterministische Abbildung der Pfadparameter auf den gemessenen Funkkanal. Der Beitrag der verteilten Streuungen wird mit Hilfe eines zirkularen mittelwertfreien Gaußschen Prozesses beschrieben. Die Modellparameter der verteilten Streuungen beschreiben dabei die Kovarianzmatrix dieses Prozesses. Basierend auf dem entwickelten Datenmodell wird im Anschluss kurz über aktuelle Konzepte für Funkkanalmessgeräte, so genannte Channel-Sounder, diskutiert. Im zweiten Teil dieser Arbeit werden in erster Linie Ausdrücke zur Bestimmung der erzielbaren Messgenauigkeit eines Channel-Sounders abgeleitet. Zu diesem Zweck wird die untere Schranke für die Varianz der geschätzten Modellparameter, das heißt der Messwerte, bestimmt. Als Grundlage für die Varianzabschätzung wird das aus der Parameterschätztheorie bekannte Konzept der Cramér-Rao-Schranke angewandt. Im Rahmen der Ableitung der Cramér-Rao-Schranke werden außerdem wichtige Gesichtspunkte für die Entwicklung eines effizienten Parameterschätzers diskutiert. Im dritten Teil der Arbeit wird ein Schätzer für die Bestimmung der Ausbreitungspfadparameter nach dem Maximum-Likelihood-Prinzip entworfen. Nach einer kurzen Übersicht über existierende Konzepte zur hochauflösenden Funkkanalparameterschätzung wird die vorliegende Schätzaufgabe analysiert und in Hinsicht ihres Typs klassifiziert. Unter der Voraussetzung, dass die Parameter der verteilten Streuungen bekannt sind, lässt sich zeigen, daß sich die Schätzung der Parameter der Ausbreitungspfade als ein nichtlineares gewichtetes kleinstes Fehlerquadratproblem auffassen lässt. Basierend auf dieser Erkenntnis wird ein generischer Algorithmus zur Bestimmung einer globalen Startlösung für die Parameter eines Ausbreitungspfades vorgeschlagen. Hierbei wird von dem Konzept der Structure-Least-Squares (SLS)-Probleme Gebrauch gemacht, um die Komplexität des Schätzproblems zu reduzieren. Im folgenden Teil dieses Abschnitts wird basierend auf aus der Literatur bekannten robusten numerischen Algorithmen ein Schätzer zur genauen Bestimmung der Ausbreitungspfadparameter abgeleitet. Im letzten Teil dieses Abschnitts wird die Anwendung unterraumbasierter Schätzer zur Bestimmung der Ausbreitungspfadparameter diskutiert. Es wird ein speichereffizienter Algorithmus zur Signalraumschätzung entwickelt. Dieser Algorithmus ist eine Grundvoraussetzung für die Anwendung von mehrdimensionalen Parameterschätzern wie zum Beispiel des R-D unitary ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) zur Bestimmung von Funkkanalparametern aus MIMO-Funkkanalmessungen. Traditionelle Verfahren zur Signalraumschätzung sind hier im Allgemeinen nicht anwendbar, da sie einen zu großen Speicheraufwand erfordern. Außerdem wird in diesem Teil gezeigt, dass ESPRIT-Algorithmen auch zur Parameterschätzung von Daten mit so genannter versteckter Rotations-Invarianzstruktur eingesetzt werden können. Als Beispiel wird ein ESPRIT-basierter Algorithmus zur Richtungsschätzung in Verbindung mit multibeam-Antennenarrays (CUBA) abgeleitet. Im letzten Teil dieser Arbeit wird ein Maximum-Likelihood-Schätzer für die neue Komponente des Funkkanals, welche die verteilten Streuungen beschreibt, entworfen. Ausgehend vom Konzept des iterativen Maximum-Likelihood-Schätzers wird ein Algorithmus entwickelt, der hinreichend geringe numerische Komplexität besitzt, so dass er praktisch anwendbar ist. In erster Linie wird dabei von der Toeplitzstruktur der zu schätzenden Kovarianzmatrix Gebrauch gemacht. Aufbauend auf dem Schätzer für die Parameter der Ausbreitungspfade und dem Schätzer für die Parameter der verteilten Streuungen wird ein Maximum-Likelihood-Schätzer entwickelt (RIMAX), der alle Parameter des in Teil I entwickelten Modells der Funkanalmessung im Verbund schätzt. Neben den geschätzten Parametern des Datenmodells liefert der Schätzer zusätzlich Zuverlässigkeitsinformationen. Diese werden unter anderem zur Bestimmung der Modellordnung, das heißt zur Bestimmung der Anzahl der dominanten Ausbreitungspfade, herangezogen. Außerdem stellen die Zuverlässigkeitsinformationen aber auch ein wichtiges Schätzergebnis dar. Die Zuverlässigkeitsinformationen machen die weitere Verarbeitung und Wertung der Messergebnisse möglich.The theme of this thesis is the estimation of model parameters of a radio channel snapshot. The main focus was the development of a general data model for the measured radio channel, suitable for both high resolution channel parameter estimation on the one hand, and the development of a robust parameter estimator for the parameters of the designed parametric radio channel model, in line with this logical work flow is this thesis. In the first part of this work an algebraic representation of observed propagation paths is developed using a ray-optical model known from literature. The algebraic framework is suitable for the description of SISO (single-input-single-output) radio transmission systems. A SISO system uses one antenna as the transmitter (Tx) and one antenna as the receiver (Rx). The derived expression for the propagation paths is also suitable to describe SIMO (single-input-multiple-output), MISO (multiple-input-single-output), and MIMO (multiple-input-multiple-output) radio channel measurements. In contrast to other models used for high resolution channel parameter estimation the derived model makes no restriction regarding the structure of the antenna array used throughout the measurement. This is important since the ultimate goal in radio channel sounding is the complete description of the spatial (angular) structure of the radio channel at Tx and Rx. The flexibility of the data model is a prerequisite for the optimisation of the antenna array structure with respect to the measurement task. Such an optimised antenna structure is a stacked uniform circular beam array, i.e., a cylindrical arrangement of antenna elements. This antenna array configuration is well suited for the measurement of the spatial structure of the radio channel at Tx and/or Rx in outdoor-scenarios. Furthermore, a new component of the radio channel model is introduced in the first part of this work. It describes the contribution of distributed (diffuse) scattering to the radio transmission. The new component is key for the development of a robust radio channel parameter estimator, which is derived in the main part of this work. The ignorance of the contribution of distributed scattering to radio propagation is one of the main reasons why high-resolution radio channel parameter estimators fail in practice. Since the underlying data model is wrong the estimators produce erroneous results. The improved model describes the so called dominant propagation paths by a deterministic mapping of the propagation path parameters to the channel observation. The contribution of the distributed scattering is modelled as a zero-mean circular Gaussian process. The parameters of the distributed scattering process determine the structure of the covariance matrix of this process. Based on this data model current concepts for radio channel sounding devices are discussed. In the second part of this work expressions for the accuracy achievable by a radio channel sounder are derived. To this end the lower bound on the variance of the measurements i.e. the parameter estimates is derived. As a basis for this evaluation the concept of the Cramér-Rao lower bound is employed. On the way to the Cramér-Rao lower bound for all channel model parameters, important issues for the development of an appropriate parameter estimator are discussed. Among other things the coupling of model parameters is also discussed. In the third part of this thesis, an estimator, for the propagation path parameters is derived. For the estimator the 'maximum-likelihood' approach is employed. After a short overview of existing high-resolution channel parameter estimators the estimation problem is classified. It is shown, that the estimation of the parameters of the propagation paths can be understood as a nonlinear weighted least squares problem, provided the parameters of the distributed scattering process are known. Based on this observation a general algorithm for the estimation of raw parameters for the observed propagation paths is developed. The algorithm uses the concept of structured-least-squares (SLS) and compressed maximum likelihood to reduce the numerical complexity of the estimation problem. A robust estimator for the precise estimation of the propagation path parameters is derived. The estimator is based on concepts well known from nonlinear local optimisation theory. In the last part of this chapter the application of subspace based parameter estimation algorithms for path parameter estimation is discussed. A memory efficient estimator for the signal subspace needed by, e.g., R-D unitary ESPRIT is derived. This algorithm is a prerequisite for the application of signal subspace based algorithms to MIMO-channel sounding measurements. Standard algorithms for signal subspace estimation (economy size SVD, singular value decomposition) are not suitable since they require an amount of memory which is too large. Furthermore, it is shown that ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) based algorithms can also be employed for parameter estimation from data having hidden rotation invariance structure. As an example an ESPRIT algorithm for angle estimation using circular uniform beam arrays (circular multi-beam antennas) is derived. In the final part of this work a maximum likelihood estimator for the new component of the channel model is developed. Starting with the concept of iterative maximum likelihood estimation, an algorithm is developed having a low computational complexity. The low complexity of the algorithm is achieved by exploiting the Toeplitz-structure of the covariance matrix to estimate. Using the estimator for the (concentrated, dominant, specular-alike) propagation paths and the parametric estimator for the covariance matrix of the process describing the distributed diffuse scattering a joint estimator for all channel parameter is derived (RIMAX). The estimator is a 'maximum likelihood' estimator and uses the genuine SAGE concept to reduce the computational complexity. The estimator provides additional information about the reliability of the estimated channel parameters. This reliability information is used to determine an appropriate model for the observation. Furthermore, the reliability information i.e. the estimate of the covariance matrix of all parameter estimates is also an important parameter estimation result. This information is a prerequisite for further processing and evaluation of the measured channel parameters

An Analysis of the Unmanned Aerial Systems-to-Ground Channel and Joint Sensing and Communications Systems Using Software Defined Radio

abstract: Software-defined radio provides users with a low-cost and flexible platform for implementing and studying advanced communications and remote sensing applications. Two such applications include unmanned aerial system-to-ground communications channel and joint sensing and communication systems. In this work, these applications are studied. In the first part, unmanned aerial system-to-ground communications channel models are derived from empirical data collected from software-defined radio transceivers in residential and mountainous desert environments using a small (< 20 kg) unmanned aerial system during low-altitude flight (< 130 m). The Kullback-Leibler divergence measure was employed to characterize model mismatch from the empirical data. Using this measure the derived models accurately describe the underlying data. In the second part, an experimental joint sensing and communications system is implemented using a network of software-defined radio transceivers. A novel co-design receiver architecture is presented and demonstrated within a three-node joint multiple access system topology consisting of an independent radar and communications transmitter along with a joint radar and communications receiver. The receiver tracks an emulated target moving along a predefined path and simultaneously decodes a communications message. Experimental system performance bounds are characterized jointly using the communications channel capacity and novel estimation information rate.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Intelligent joint channel parameter estimation techniques for mobile wireless positioning applications

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Mobile wireless positioning has recently received great attention. For mobile wireless communication networks, an inherently suitable approach is to obtain the parameters that are used for positioning estimates from the radio signal measurements between a mobile device and one or more xed base stations. However, obtaining accurate estimates of these location-dependent channel parameters is a challenging task. The focus of this thesis is on the estimation of these channel parameters for mobile wireless positioning applications. In particular, we investigate novel estimators that jointly estimate more than one type of channel parameters. We rst perform a comprehensive critical review on the most recent and popular joint channel parameter estimation techniques. Secondly, we improve a state-of-the-art technique, namely the Space Alternating Generalised Expectation maximisation (SAGE) algorithm by employing adaptive interference cancellation to improve the estimation accuracy of weaker paths. Thirdly, a novel intelligent channel parameter estimation technique using Evolution Strategy (ES) is proposed to overcome the drawbacks of the existing iterative maximum likelihood methods. Furthermore, given that in reality it is di cult to obtain the number of multipath in advance, we propose a two tier Hierarchically Organised ES to jointly estimate the number of multipath as well as the channel parameters. Finally, we extend the proposed ES method to further estimate the Doppler shift in mobile environments. Our proposed intelligent joint channel estimation techniques are shown to exhibit excellent performance even with low Signal to Noise Ratio (SNR) channel conditions as well as robust against uncertainties in initialisations.EPSRC and Cambridge Silicon Radi

Development and verification of semi-blind receiver structures for broadband wireless communication systems

The increasingly high demands for high data rate wireless communication services require spectrum- and energy-efficient solutions. In this thesis, a number of energy-efficient semi-blind receiver structures are proposed to perform Doppler spread estimation, channel estimation and equalisation for broadband wireless orthogonal frequency division multiplexing (OFDM) systems. A real-time wireless communication testbed is developed to verify the proposed semi-blind receiver structures. In the first contribution, a semi-blind Doppler spread estimation and Kalman filtering based channel estimation approach is proposed for wireless OFDM systems. A short sequence of reference data is carefully designed and applied as pilot symbols for Doppler spread estimation and channel estimation initialisation of the Kalman filter. Then the estimates of inter-carrier interference (ICI) caused by Doppler spread are gathered into the equivalent channel model and compensated for through channel equalisation, which dramatically reduces the computational complexity. The simulation results show that the proposed approach outperforms the conventional pilot aided Doppler spread and channel estimation schemes. In the second contribution, a semi-blind Doppler spread estimation and independent component analysis (ICA) based equalisation scheme aided by non-redundant precoding is proposed for wireless multiple-input multiple-output (MIMO) OFDM systems. A number of reference data sequences are selected from a pool of orthogonal sequences for two purposes. First, the reference data sequences are superimposed in the source data sequences through non-redundant linear precoding to enable the Doppler spread estimation by minimising the sum cross-correlation between the compensated signals and the rest of the orthogonal sequences in the pool. Second, the same reference data sequences are applied to eliminate the phase and permutation ambiguity in the ICA equalised signals. Simulation results show that the proposed semi-blind MIMO OFDM system can achieve a bit error rate (BER) performance which is close to the ideal case with perfect channel state information (CSI). In the third contribution, a real-time wireless communication testbed is developed with a vector signal generator, a vector signal analyser and a pair of antennas, to verify the effectiveness of the proposed receiver structures over the air in different environments such as Reverberation chamber and office area. Measurement results show a good match with simulation results. Also, a pilot is employed for three purposes at a semi-blind receiver: time synchronisation, Doppler spread estimation and Kalman filtering initialisation, which is an extension of the work in the first contribution