7:00 a.m. - 1:00 p.m.: Registration, Falls Church Foyer
8:00 a.m. -11:00 a.m.: Morning Refreshment Break, Hospitality Zone
8:30 a.m. - 8:45 a.m.: Welcome and Opening Remarks, Dr. Michael Buehrer, Director, Wireless @ Virginia Tech, East/West Falls Church Room
8:45 a.m. - 9:45 a.m.: Keynote Address, Paul Tilghman, Microsystems Technology Office (MTO), Program Manager, East/West Falls Church Room
9:45 a.m. - 10:00 a.m: Break
10:00 a.m. - 11:30 a.m.: Panel Session, East/West Falls Church Room
Title: 5G: Coming of Age of Cognitive Radio?
Despite the continued popularity of research in "cognitive radio", the cognitive radio research literature has largely narrowed the topic to focus solely on primary/secondary spectrum reuse. Further, the perception has grown that broader applications of artificial intelligence in communication systems and networks are not ready for commercial application. The emergence of the next generation (5G) of cellular systems, though, finally seem to acknowledge the importance of several key ideas that have been at the heart of the cognitive radio concept since its inception. First and foremost, 5G systems will support wide array of spectrum bands, ranging from current sub-GHz cellular bands all the way to mmWave bands, including licensed, shared, and unlicensed spectrum. The problem of co-existence across different types of bands and licensing regimes has always been a central application of cognitive radio. Second, the sheer complexity of operating a massive network across different bands highlights the need to push intelligence to the edge nodes, which has been another key component of cognitive radio research. In this panel, we bring together experts to discuss the latest advancements in cognitive radio research in the context of emerging 5G systems. While it is obviously not prudent to equate cognitive radio with 5G, there are many parallels that one can draw between these two systems/technologies. The goal of this panel is to discover and discuss these parallels.
Panel Session Members: Dr. Joseph Mitola III, Director, Information Systems Laboratory, Hume Center, Dr. Jeffrey Reed, Willis G. Worcester Professor, Founding Director of Wireless@Virginia Tech, Paul Tilghman, Microsystems Technology Office (MTO) Program Manager
Moderator: Dr. Allen MacKenzie
11:30 a.m. - 12:00 Noon: Wireless Project Presentation and Demo, Dr. Michael Buehrer, Dr. Jeffrey Reed
12:00 Noon - 1:00 p.m.: Lunch, Falls Church Foyer and East Falls Church Room
1:00 p.m. - 2:00 p.m.: Digital Poster Session, Dessert, Hospitality Zone
2:00 p.m - 5:00 p.m.: Tutorial Sessions
5:30 p.m. - 7:30 p.m.: Poster Session/Beer and Pizza Reception
In a hurry to get something on the air, you attach a telescoping whip antenna (or a long wire, or a paper clip, or ...) to a radio. There's no way the antenna can be resonant or impedance-matched, yet it works. Why? What is lost (or gained...) by not using a "proper" antenna? Approaching this from a design perspective: How does one specify an antenna system and associated electronics that are "good enough" and not larger or more expensive than necessary? This tutorial begins with a brief review of the fundamentals of antennas, noise, and propagation; and culminates in an analysis of sensitivity (i.e., the receive case) and delivered power density (i.e., the transmit case) applicable to all kinds of radio systems. Application examples include cellular and LMR handsets, direct broadcast satellite TV, and HF-band near-vertical incidence skywave (NVIS) systems. Topics addressed along the way include: Equivalent circuit representations of antennas, characterization of internal and external noise in radio systems; conjugate, reflection less, and lossy impedance matching; appropriate uses of baluns and impedance tuners; and the common question "How small can an antenna be?"
Game theory is a field of applied mathematics that describes and analyzes interactive decisions. Its ability to model individual, independent decision makers whose actions potentially affect others makes game theory particularly suitable for studying the environments in which cognitive radios operate. In this tutorial, we will describe some of the main applications of game theory to cognitive networks. These include: models of cooperation and coexistence among cognitive radios and between cognitive radios and legacy users; spectrum auctions and other economic models; and the modeling of partial or incomplete information in decision making. Game theory is one of the main tools in the rigorous analysis of interactions among cognitive radios. The intended audience for this tutorial includes post-graduate students, academic faculty, and industrial researchers who want to be able to read and understand published research that applies game theory to the analysis and design of cognitive networks, as well as those who are considering using game theory in their own research. The tutorial does not assume knowledge of game theory; basic concepts in cooperative and noncooperative games will be introduced as they are used. We will address the following topics in this tutorial: motivation: a case for game theory in cognitive radio research; game theory basics; power control and interference games; distributed channel assignment and topology control games; cooperative models of dynamic spectrum access; real time spectrum markets; and mechanism design: truth telling and incentive compatibility.
The presenter has significant experience in applying game theory to wireless communications problems. He co-authored the book Game Theory for Wireless Engineers in 2006 and has published numerous papers on game theoretic modeling of cognitive radios. He has presented tutorials on cognitive networks at CROWNCOM, MobiCom, and TridentCom.
This tutorial provides an overview of the fundamental security principles and privacy mechanisms relevant to wireless networks. The tutorial includes discussions on important symmetric and asymmetric cryptosystems; Advanced Encryption Standard (AES); privacy-preserving authentication protocols; IEEE 802.11i; and security issues in IoT.
3:00 p.m. - 3:15 p.m.: Refreshments Break
5:15 p.m. - Tutorials End
5:30 p.m. - 7:30 p.m.: Beer and pizza reception
7:30 a.m. - 11:00 a.m.: Morning Refreshment Break, Hospitality Zone
8:00 a.m. - 8:15 a.m.: Introduction of Keynote Speaker, Dr. Jeffrey Reed
8:15 a.m. - 9:15 a.m.: Keynote Address, Mrs. Ellen Purdy, Title: Spectrum Access Research and Development
9:15 a.m. - 12:15 p.m.: Tutorial Sessions 2A, 2B, 2C
Signal processing consists of the theory and tools that form the assumed background knowledge and skills for the implementation and testing of algorithms that are used in many applications. Examples are the analysis, coding, and synthesis of speech signals, the detection of pathologies in EEG and ECG, or of changes in computer code executed on embedded processors, to name just a very few. One of the major areas where signal processing is used is in communications. Signals need to be coded with information, prepared for use of available channels, extracted, cleaned up by mitigation of impairments, and ultimately deliver the transmitted information.
The following topics and concepts play an important role in the processing of communication signals and will be reviewed in this tutorial:
This tutorial investigates spectrum operations in contested and congested RF environments, to include communications and radar. The presentation investigations various analytic approaches, including information-theoretic perspectives, control-theoretic perspectives, and application of a variety of machine learning techniques that support these analyses. For example, the talk will investigate how state estimation of the various actors in the electromagnetic environment enables more effective spectrum operations from a control-theoretic perspective, bounds on the ability to use machine learning techniques to estimate that state from an information-theoretic perspective, and how use of these noisy models can be used to develop better interaction policies for agents interacting in the spectrum.
Radio frequency (RF) front ends are nonlinear systems that have nonlinear frequency response that can impair receiver performance by harmful adjacent channel interference in non-intuitive ways. In dynamic spectrum access scenarios, where heterogeneous transceivers access shared spectrum, poor RF selectivity compromises communications performance. This tutorial addresses the technological challenges in receiver-centric wireless network design and develops an analytical framework for quantifying the implications of RF front-end nonlinearity on network performance, utilization, and fairness. This tutorial will further provide deep technical insights into nonlinear adjacent channel interference management, avoidance, and cancellation for next generation dynamic spectrum access networks.
The tutorial is organized in four parts. The first part introduces the fundamental analytical framework for characterizing and quantifying the impact of RF front-end nonlinearity on dynamic spectrum access system performance. We present model specific spectral characterization to describe the phenomena of third order intermodulation, cross-modulation and desensitization of the receiver front-end nonlinear distortion, necessary for adjacent channel co-existence analysis. Further, we analyze the impact of nonlinearity on achievable rates and Bit Error Rate performance and provide a generalized framework for comparative quantification of disparate receiver types. The second part presents a comprehensive wireless network management framework and strategies that account for the RF imperfections and diversity of heterogeneous wireless devices. The third part establishes the fundamentals of nonlinear interference between symbols of adjacent channels and addresses the scalability and network level mechanisms for nonlinear adjacent channel interference avoidance. The fourth part details the development of a test-bed to mimic the basic functionalities of SAS, which will serve as a unique platform to conduct experiments for hypothetical test cases and practical scenarios. The test-bed is built using 8 Universal Software Radio Peripheral (USRP) devices in conjunction with a channel emulator and the required computational resources to run the algorithms.
Example practical applications of the topics covered in this tutorial are in the design of spectrum access schemes for the 3.5 GHz band and the recent efforts to open AWS-3 band for sharing in the US, but the same principles apply to any spectrum sharing band. Overall, this tutorial introduces the fundamentals of receiver-centric analysis, frameworks and algorithms critical to the design, development, testing and successful deployment of next generation dynamic spectrum access networks.
12:15 p.m. - Symposium Ends