TUTORIAL 1

Smart Antennas, MIMO & Space-Time Codes

by Dr David Gesbert

Signal and Image Processing Group

Dept of Informatics at the University of Oslo

Overview

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1. Brief overview of Smart Antennas technology

1.1) Fundamentals of Smart antennas and MIMO (multi-in multi-out) wireless links

1.2) Why MIMO?

2. Multi-antenna signaling techniques

2.1) MIMO Spatial Multiplexing (BLAST-type) versus Diversity, Beamforming, Space Time Codes

2.2) Key features and limitations

2.3) What applies where?

3. Adaptivity in multi-antenna signaling and coding techniques

3.1) Understanding and tracking the channel environment

3.2) Switching strategies

4. MIMO channel modeling

4.1) Fundamentals

4.2) Recent measurements

5. MIMO in Broadband Wireless Networks

6. Performance evaluation (Case study)

7. Standardization issues

Biography of David Gesbert:

D. Gesbert obtained the Ph.D degree from Ecole Nationale Superieure des Telecommunications ( ENST "Telecom Paris" ), Paris , France, in 1997. From 1993 to 1997, he was with France Telecom Research (CNET) , Paris, where he was involved in the development and study of receiver algorithms for digital radio communications systems, with emphasis on blind signal detection. From April 1997 to October 1998, he has been a postdoctoral fellow at the Smart Antenna Research Group of the Information Systems Laboratory , Stanford University. From April 1997 to April 1998, he has been the recipient of a French Defense DGA/DRET postdoctoral fellowship.

In October 1998, he took part in the founding team of Iospan Wireless Inc , formerly Gigabit Wireless Inc, San Jose, Ca.,a startup company designing high-speed wireless internet access networks using smart antennas (MIMO), OFDM, and other state-of-the-art applied wirelessresearch. In 2001, he joined the Signal and Image Processing Group , Dept of Informatics at the University of Oslo as an adjunct associate professor in parallel to his other activities. His research interests are in the area of signal processing for digital communications, smart antennas and MIMO, multi-usercommunications,link layer scheduling and resource allocation, high-speed wireless data networks.

D. Gesbert has published over 40 papers and several patents all in the area of signal processing, communications, and wireless networks. He is co-editing the 2003 special issue of IEEE JSAC devoted to MIMO wireless systems.

TUTORIAL 2

Blind source separaration: principles and applications

by Dr J.F. Cardoso

CNRS France

Abstract

Independent component analysis (ICA) is an emerging data processing technique by which a random process is decomposed into linear components which are `as independent as possible'. It is also known as `statistical source separation' (SSS) in the fields of signal and image processing. The model of linear, independent components is general enough to encompass many application fields: array processing, smart antennas, multi-microphone audio processing (the cocktail-party problem), spectral anlaysis, image processing (connexions to wavelets), biomedical signals (functional MRI, EKG,...), etc.

This talk will open by presenting three applications of ICA/SSS, by discussing how the ICA model can actually fit real data, and in which ways it differs from (or opposes to) PCA (principal component analysis). Next, I will describe the statistical ideas underlying the ICA model and their relationships. Starting from the maximum likelihood (ML) principle, the ICA problem is recast as a problem of optimizing information-theoretic objective functions. Depending on prior assumptions, the objective is statistical independence as measured by the mutual information, minimum entropy (in the Shannon sense), or maximum non Gaussianity. All these ideas will be presented in the light of `information geometry': a geometric framework which offers a unifying view of all the key concepts.

Time permitting, I will also discuss various the algorithmic ideas which have been developped for turning theoretical objective functions into tractable criteria, some algorithmic principles (equivariant estimators, joint diagonalization,...) and some aspects of the achievable performance of blind signal separation.

Biography of Jean-Francois Cardoso

Jean-Francois Cardoso is with the French `Centre National de la Recherche Scientifique' (CNRS), in the Signal and Image Processing Dept of Ecole Nationale Superieure des Telecommunications (ENST, Paris). His research area is statistical signal processing. Since 1989, he has been extensively working on all aspects of blind source separation and independent component analysis. In 2001, he started a collaboration with astronomers for the statistical analysis of astronomic data. More details can be found at: http://www.tsi.enst.fr/~cardoso/

TUTORIAL 3

Image & Video Quality Assessment

by Dr Azeddine Beghdadi

CNRS France

Abstract

With the increasing use of digital video compression and transmission systems image quality assessment has become a crucial issue. In the last decade, there have been proposed numerous methods for image distortion evaluation inspired from the findings on Human Visual System (HVS) mechanisms. This tutorial aims at presenting the well-known image quality measures and gives the state of art in this field. The image quality enhancement will be also addressed and the notion of perceptual irrelevancy will be introduced and discussed. This tutorial is organized in three parts :

-Basic notions and tools for designing an image quality measure

(HVS,contrast,color,perceptual irrelevancy)

- Image quality assessment

- Image and video enhancement

Biography of Dr. Azeddine Beghdadi

Dr. Azeddine Beghdadi is currently Full Professor at the University of Paris 13 (Institut Galilée) and a researcher at L2TI laboratory where he does all his research in Image Processing (Image Enhancement, Segmentation, Image compression, Image Quality, Medical Imaging, and Physics and Bio-inspired Models for Image Analysis). He received an education in physics ( applied and theoretical optics). He obtained his "Maitrise" in Physics, and Diplome d'Etudes Approfondies in Optics and Signal Processing from University Orsay-Paris XI in June 1982 and June 1983 respectively. He also obtained his PhD in Physics (Optics and Signal Processing) from University Paris 6 in June 1986. Prof. Beghdadi worked at different places including the "Groupe d'Analyse d'Images Biomédicales" (CNAM Paris )and "Laboratoire d'Optique des Solides" (University of Paris 6).From 1987 to 1989, he has been a "Assistant Associé" (Assistant Professor) at University Paris 13. During this period Prof. Beghdadi was also with LPMTM CNRS Laboratory working on Scanning Electron Microscope (SEM) materials image analysis. From October 1989 until December 1997, he was Maître de Conférences (Associate Professor). All his research activities where at LPMTM CNRS Laboratory at University Paris 13 in the area of Image Processing Applications for Mechanical Problems. He then received his "Habilitation à Diriger des Recherches" from University Paris 13 in May 1994. That was an achievement of ten years of research in the area of Image Processing Fundamentals (Image Enhancement, Non linear Filtering, Segmentation, image analysis ) and their applications to Physical and Mechanical problems (Multifractal and Entropic Analysis of Disordered Heteregeneous Media - Measurement of Mechanical Deformation from Scanning Electron Microscope Images).He was a visiting Professor at University of Geneva in Switzerland, at Queensland University of Technology in Australia and at Tampere University of Technology in Finland. Currently he is a visiting Professor at ENST-Paris for one year. Prof. Beghdadi published over 28 international journal papers and over than 60 conference papers.

TUTORIAL 4

Wireless Software: What is it and how to develop it

by Dr Qusay Mahmoud

School of Computing Science, Simon Fraser University,

Vancouver, Canada

Abstract:

Most Internet technologies are designed for desktop and large computers running on reliable networks with relatively high bandwidth. Hand-held wireless devices, on the other hand, have a more constrained computing environment. They tend to have less memory, less powerful CPUs, different input devices, and smaller displays. The Wireless Application Protocol (or WAP), which is a specification developed by the WAP Forum, takes advantage of the several data-handling approaches already in use. Developing wireless applications using WAP technologies is similar to developing web pages with a markup language because it is browser based. Another approach to developing wireless applications is to use the Mobile Information Device Profile (MIDP).

With either WAP or MIDP, the Java programming language plays an important role. In WAP, Java Servlets and Java Server Pages (JSPs) can be used to generate Wireless Markup Language (WML) pages dynamically, and in MIDP, applications (also called MIDlets) are written in Java.

The tutorial will help participants understand the different technologies that can be used to develop wireless applications for hand-held devices.

The list of major topics to be covered in this tutorial includes:

- Handheld Device Markup Language (HDML)

- Compact HTML (cHTML)

- Wireless Application Protocol (WAP)

- Java 2 Micro Edition (J2ME)

- Kilo Virtual Machine (KVM)

- Mobile Information Device profile (MIDP)

- Palm Programming with Java

- other technologies for wireless computing (Qualcomm's BREW and

Microsoft's Stinger)

- Software engineering issues

- Security Issues

- Useful Resources

Objective: participants will acquire knowledge about wireless programming techniques in general and Java programming for mobile devices in particular. They will know about the different techniques that can be used for wireless programming and how/when to use them. Issues in User Interface design for handheld devices will be discussed.

Background: knowledge of the Java programming language.

Biography of Dr Qusay Mahmoud

Name: Qusay Mahmoud

Affiliation: School of Computing Science, Simon Fraser University,

Vancouver, Canada

Email: qmahmoud@cs.sfu.ca

Phone and address:

School of Computing Science

Simon Fraser University

Burnaby, B.C., V5B 1H4 Canada

(604) 291-4070

Qusay H. Mahmoud is a faculty member in the School of Computing Science at Simon Fraser University, Vancouver, Canada. He has published dozens of articles, and two books: 'Distributed Programming with Java'(Manning Publications, 1999), and 'Learning Wireless Java' (O'Reilly, 2002). Qusay has presented tutorials at a number of international conferences worldwide.

TUTORIAL 5

Agreement problems in distributed computing

by Dr Rachid Guerraoui

Swiss Federal Institute of Technology (EPFL)

Lausanne

Abstract

This tutorial will address the fundamental problems underlying reaching agreement in a distributed system. Variants of this problem are at the heart of practical distributed systems like censor value aggregations (e.g., in military applications), transactional processing (e.g., in financial applications) as well as highly available systems (e.g., in air traffic control applications). The tutorial will cover some of the most fundamental results in solving agreement problems. It will also bridge the gap between this problem and the problem of error correcting codes in signal processing as well as the connectivity problem in algebraic topology.

Biography of Dr Rachid Guerraoui

Rachid Guerraoui is professor in computer science at the Swiss Federal Institute of Technology in Lausanne (EPFL) where leads the Distributed Programming Laboratory. He has published more than 100 papers in the field of distributed computing and has been member of all program commitees of significant conferences in the area. He also program chair of ACM Middleware, IEEE SRDS, IEEE ICDCS and ECOOP. Most of his papers are available through lpdwww.epfl.ch

TUTORIAL 6

E-Service Platforms- Concepts and Solutions

By Zahir Tari

Abstract

:

An E-service can be any service that can be accessed across the network using some standard protocol. E-services are a rapidly growing area with enormous potential for building systems that deal with complex dynamic environments. There are three fundamental benefits that advanced E-services bring to enterprises. Firstly, they provide more automation by enabling applications to seamlessly interact with other applications within and outside enterprise boundaries by reducing the amount of human interaction needed to exchange or transfer information, thus enabling an extra degree of automation. For example, intelligent software agents wrapped as E-services can be used to automate the negotiation of services between businesses or in triggering the other E-services. Secondly, E-services provide more federation as service providers focuses on creating and offering value-added services; they are more inclined to outsource non-strategic parts of their businesses to external service providers. This allows complex business services to be federated into smaller sub-services across several enterprises. Finally, E-services provide more dynamism. The extra automation and federation make services more dynamic, as one can dynamically discover new E-services with the right set of Quality of Service and bind to them at run-time.

Traditional E-services are customized applications, however there is a clear move away from tightly coupled monolithic systems and towards loosely coupled, dynamically bound components. This move

brings unprecedented benefits to enterprises as they reduce the amount of human interaction; focus on creating value-added services; and dynamically discovering services.

E-services are used for large scale enterprise integration as they do integrate emerging web service standards, such as UDDI (for Universal Discovery Description and Integration), SOAP (for Simple Object Access Protocol) and WSDL (for Web Service Description Language; do enable integration of processes across enterprise. E-service platforms support several key features, such as Flexible communication: Eservice platforms use SOAP (Simple Object Access Protocol) as a core layer to enable flexible communication across different E-services. Contrary to existing communication protocols (such us IIOP, RMI), SOAP is not restricted to any specific ?format? for data. Information is exchanged as documents (i.e. XML documents) and therefore requests are directly transmitted using specific bindings (such as HTTP POST). Dynamic Service Discovery - E-Services providers allow their clients' applications to dynamically look up and interact with those services, even with no prior knowledge of the services. · Dynamic Service Composition - This is the process of creating added-value services at run time from a set of service components. This is particularly important because of the highly dynamic environment of E-services where new services are added on daily basis. E-Services workflows, although conceptually similar to traditional workflow techniques, they have very different concepts and requirements. For example, in an E-service environment, there is typically no fixed ?organizational model?.

This tutorial will provide all the necessary (technical) details which enable participants to understand the underlying concepts and solutions to the three issues listed above, namely Communication with SOAP, Service Discovery and Service Composition.

Biography of Dr Zahir Tari

Professor Zahir Tari is the leader of the activity unit Distributed Systems & Networking Systems at RMIT University. He worked in the area of middle wares and wrote/edited several books. His research is published in prestigious journals (such ACM Transactions and IEEE Transactions on Distributed Systems). He has also be consultant for national German bank for several years and has successful grants with Australian industry (in the area of E-Services). Finally, Dr Tari has been general chair and program committee chair of several international conferences (which deal with issues of e-service

platforms).

More details about Professor Tari can be found at

http://www.cs.rmit.edu.au/~zahirt

http://www.cs.rmit.edu.au/eCDS