Dublin, Ireland 17-20 April 2007
IEEE DySpan 2007
Program Information Special Events Speaker Information Registration Venue/Hotel Info IEEE Travel Visa Information General Information Committees About COMSOC
PROGRAM INFORMATION


Please click here to review the final DySPAN program
PROPOSED CONFERENCE AGENDA
TUTORIALS
KEYNOTE INFORMATION

 
Tuesday 17 April
9:00 - 12:00
AM TUTORIAL / DEMONSTRATIONS SESSION 1
13:00 - 17:00
PM TUTORIALS / DEMONSTRATIONS SESSION 2
18:30 - 20:00
WELCOME RECEPTION AT TRINITY COLLEGE
Wednesday 18 April
8:30 - 12:00
GENERAL SESSION/OPENING KEYNOTE
12:00 - 13:00
LUNCH
13:00 - 15:00
TECHNOLOGY AND POLICY TRACKS
13:00 - 17:50
POSTER SESSIONS
14:20 - 15:30
TABLETOP DEMONSTRATIONS
15:00 - 15:30
NETWORKING BREAK
15:30 - 18:00
TECHNOLOGY AND POLICY TRACKS
17:10 - 18:20
DEMONSTRATIONS “HAPPY HOUR”
18:30 - 21:00
CONFERENCE BANQUET
Thursday 19 April
8:00 - 12:00
GENERAL SESSION
12:00 - 13:00
LUNCH
13:00 - 18:00
TECHNOLOGY AND POLICY TRACKS
14:20 - 15:30
DEMONSTRATIONS (COLLABORATIONS)
15:00 - 15:30
NETWORKING BREAK
15:00 - 18:00
TECHNOLOGY AND POLICY TRACKS
17:10 - 18:20
DEMONSTRATIONS “HAPPY HOUR”
Friday 20 April
8:00 - 12:00
CLOSING GENERAL SESSION
   
   
   

Tutorials   17 April 2007

Tutorial 1
8:30 AM – 12:00 PM
The Policy and Practice of Spectrum Trading


Dr. Martin Cave (Warwick Business School)
Mr. Darrin Mylet (Cantor Fitzgerald)

This tutorial provides an in-depth overview of the current state and future trends in secondary spectrum markets and trading, from two of the leading experts in the field.

Martin Cave is Professor and Director of the Centre for Management under Regulation, Warwick Business School. Until 2001 he was Professor of Economics at Brunel University. He specialises in regulatory economics, especially of the communications sector. He has advised a number of Regulatory Agencies in Telecommunications and Broadcasting. As well as his academic work he has also undertaken studies for the European Commission and advised regulatory agencies. He was a member of the Competition Commission from 1996 to 2002. He is the author of the Independent Review of Spectrum Management (2002) for the UK Government, co-author of Understanding Regulation (1999) and co-editor of the Handbook of Telecommunications Economics (Vol. 1, 2002, Vol. 2, 2005).


Darrin Mylet is Vice President-Wireless Services for Cantor Fitzgerald. Mr. Mylet joined Cantor Fitzgerald in 2003 to grow the firm’s unique trading technologies and business objectives relative to wireless. Mr Mylet is working with both the public and private sectors in facilitating the trading of radio frequency rights and tower assets among telecommunications operators, spectrum/tower owners, equipment vendors, municipalities and government agencies. Further, entities can lease or buy dormant or partially used licensed spectrum rights, tower assets and tower space for private or public use which should increase broadband per capita in specific jurisdictions. Cantor Fitzgerald will enable this using the firm’s unique, proven, scalable and un-biased trading and proprietary systems.

Prior to joining Cantor-Fitzgerald, Mr. Mylet was with Radiant Networks, a U.K. based pioneer in “physical mesh” broadband wireless equipment vendor, where he was Vice President of Sales & Marketing-Americas from 2000-2003. Prior to this position, Mr. Mylet was an executive with Worldcom/MCI from 1997 to 2000.  From 1992 to 1997, Mr. Mylet was with GTE Corporation (now Verizon). Mr. Mylet earned his bachelor’s degree in economics from Indiana University, Bloomington, IN.  Mr. Mylet was recently named to the White House led Department of Commerce Spectrum Policy Task Force in October of 2006. Mr. Mylet has had the honor of speaking at numerous industry events including WCAI, USTA, SUPERCOMM, WISPCON, ISPCON,EU/UK SPECTRUM TRADING, BWWF, NTIA, NATPE & CTIA.


Tutorial 2
1:30 PM – 5:00 PM
Game Theory in the Analysis and Design of Cognitive Radio Networks


Dr. James Neel (Virginia Tech)

This tutorial presents the relationship between game theory and the design and analysis of cognitive radio networks as most frequently encountered in today’s cognitive radio literature. The subject matter ranges from basic game theoretic concepts – e.g., the concept of a game and Nash equilibria – to more esoteric material typically covered in graduate game theory courses, but which are critical to understanding state-of-the-art dynamic spectrum access networks. This tutorial illustrates how concepts from game theory are being used to shape the design of dynamic spectrum access networks to yield powerful low-complexity cognitive radio algorithms, e.g., power control, dynamic frequency selection, spectrum trading, sensor network formation, routing, and node participation.

Biography

In 2006 James “Jody” Neel received his PhD in Electrical Engineering from Virginia Tech for his dissertation on the topic of “Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms.” At Virginia Tech, he was an IREAN Fellow advised by Dr. Jeffrey H. Reed. He has an extensive history of involvement with software radio, with twenty publications on software radio, including two textbook chapters on data conversion and the history of software radio in Dr Reed’s Software Radio: A Modern Approach to Radio Engineering and another chapter on analyzing cognitive radio interactions in Spectrum Efficiency and Cognitive Radio Technology edited by Dr Bruce Fette. Jody also received awards for his 2002 and 2004 SDR Forum papers on applying game theory to the analysis of cognitive radio networks.                                        

Contents

Cognitive radio is a frequently touted platform for implementing dynamic spectrum access algorithms. In the envisioned scenarios, radios react to observations of their environment and change their operation according to some goal driven algorithm While potentially yielding tremendous gains in performance, the adaptations of radios also change the environment for other cognitive radios spawning an interactive decision process. In such a scenario, algorithms which have desirable properties over a single link can result in catastrophic failures when numerous cognitive radios implement the same algorithm in a network setting.

To address these issues, many researchers have turned to game theory to model and analyze the interactions of cognitive radios and to improve the design of networks. However, game theory is a topic that falls well outside of traditional engineering curricula. Lacking knowledge of concepts such as Nash bargaining solutions, mixed strategy equilibria, Shapley values, and potential games, the typical engineer or spectrum regulator faces a daunting task to just understand what researchers are proposing.

Intended to provide attendees with knowledge of the most important game theoretic concepts employed in state-of-the-art dynamic spectrum access networks, this tutorial presents the relationship between game theory and the design and analysis of cognitive radio networks as most frequently encountered in today’s cognitive radio literature. The subject matter will range from basic game theoretic concepts – e.g., the concept of a game and Nash equilibria – to more esoteric material typically covered in graduate game theory courses, but which are critical to understanding state-of-the-art dynamic spectrum access networks. This tutorial will also illustrate how concepts from game theory are being used to shape the design of dynamic spectrum access networks to yield powerful low-complexity cognitive radio algorithms. To provide a more familiar learning environment and an appreciation of how game theory applies to cognitive radio, all concepts in this tutorial will be illustrated with examples frequently encountered in the cognitive radio literature – e.g., power control, dynamic frequency selection, spectrum trading, sensor network formation, routing, and node participation.

This tutorial is arranged into six sections of varying length. The first portion of this tutorial will cover basic concepts from game theory and their application to cognitive radio networks. This includes a summary of the analysis and design challenges posed by cognitive radio networks, the basic components of a game model, and how and when game theory can be applied to cognitive radio networks. To aid the discussion of later more in-depth material, a brief review of mathematical concepts fundamental to the application of game theory to cognitive radio networks will also be presented.

The second and third sections will cover the application of game theoretic equilibrium concepts to cognitive radio networks. As researchers have proposed both non-cooperative and cooperative approaches to implementing cognitive radio networks, this section covers concepts such as Nash equilibria, mixed strategy equilibria, strong equilibria, and the core. Techniques for evaluating the desirability of these equilibria, such as Pareto efficiency and Shapley values, are then presented.

The fourth section addresses the notion of time and imperfections and how they can be incorporated into game models of cognitive radio networks including extensive form games, repeated games, trembling hand games, and Markovian games. The fifth section examines how the analysis techniques of the preceding sections can be leveraged to design cognitive radio networks that yield desired behavior with schemes for punishment and reward and by designing for implicit cooperation with potential games. The tutorial concludes with a summary of the critical concepts presented and speculation on the future role of game theory in the design and regulation of dynamic spectrum access networks.

 

Tutorial 3
1:30 PM – 5:00 PM
End-to-End Reconfigurability – The European E2R II Programme


Dr. Didier Bourse (Motorola Labs)
Dr. Markus Muck (Motorola Labs)
Dr. Klaus Moessner (University of Surrey)
Mr. David Grandblaise (Motorola Labs)
Pr. Panagiotis Demestichas (University of Piraeus)
Dr. Pieter Ballon (University of Brussels)

This tutorial presents some of the most promising developments relative to cognitive radio systems developed by the European E2R II Programme on End-to-End Reconfigurability. Tutorial topics include advanced radio resource management, flexible spectrum management, dynamic network planning and management, and the cognitive pilot channel. The objective of the E2R II research programme is to devise, develop and trial an architectural design for adaptive communication systems that offers an expanded set of operational choices to users, applications and service providers, operators, manufacturers and regulators in the context of heterogeneous mobile radio systems composed of cellular, wireless local area, broadcast and other technologies.

Contents

1. From Software Defined Radio to End-to-End Efficiency

1.1) Research and Developments on SDR, CR and Reconfigurable Radio and Networks
1.2) EU FP6 E2R Programme in a Nutshell
1.3) E2R Programme Key Technical Achievements

2. Business Models and Standardization/Regulation Perspectives for Cognitive Radio Systems

2.1) Unified Business Model (UBM)
2.2) Key UBM Instantiations (DSA, CPC, White Plastic…)
2.3) Technology Roadmaps towards Cognitive Networks and Reconfigurable Equipment
2.4) Regulatory and Standardization Perspectives

3. Efficiency Enhancement for Radio Resource and Spectrum

3.1) Managing Spectrum and Radio Resources in a Reconfigurability and Cognitive Network Context
3.2) Functional Architecture for Managing Radio Resources and Spectrum in a Reconfigurability Context

4. Joint Radio Resource Management

4.1) Problem Statement
4.2) Solution Algorithms for the Control Domain and Machine Learning Functionality
4.3) Key Results
4.4) Enhancements in the Direction of Cognitive Technologies

5. Advanced Spectrum Management

5.1) Description of Problems Addressed, Technical and Economic Perspectives, Single and Multi-Operator Scenarios
5.2) Solution Algorithms and Machine Learning Functionality
5.3) Key Results
5.4) Enhancement

6. Dynamic Network Planning and Management

6.1) Description of Problem, Distributed and Semi-Distributed Solutions
6.2) Input Description: Context, Profiles, Policies
6.3) Algorithms for the Solution: Bayesian Networks, Greedy Algorithms, Mid-term Optimisation Algorithms, Pattern Matching Techniques
6.5) Key Results
6.6) Demonstration Samples
6.7) Enhancements in the Direction of Cognitive Networks and Autonomics

7. Key Challenges to enable the Seamless Experience

7.1) Reconfigurability Time Frames
7.2) Next Research Steps