Wireless technology differs from other electrical engineering technologies in that spectrum is highly regulated around the world.
At present in the US there is no commercial use of the radio spectrum for mobile/cellular systems above 3 GHz and no commercial use above 85 GHz. Indeed, FCC now implicitly forbids all commercial use above 95 GHz as well as mobile use about 3 GHz, something that no doubt puts a damper on private funding of research in these areas. This presentation comes a few days FCC is expected to make its first decision on permitting mobile use in the 24-80 GHz region. While some firms are pressing for movement of the present 95 GHz boundary, it remains to be seen if FCC is also acting on that - update at presentation!. It will deal with both the technical challenges of such spectrum use, thought to have been impractical for mobile applications until a few years ago, as well as the spectrum policy challenges. It will also touch on the impact on private capital formation in the wireless technology area of regulatory uncertainties that cast doubt on timely technology transfer to commercial markets.
Michael Marcus is a native of Boston and received S.B. and Sc.D. degrees in electrical engineering from MIT. Dr. Marcus has a distinguished career in the communications policymaking, having served with the FCC from 1979 until 2004, where he helped lead major initiatives in spectrum policy reform in such areas as spread spectrum/CDMA, millimeterwaves, ultrawideband, and cognitive radio. Dr. Marcus was instrumental in opening Wi-Fi spectrum and was a senior advisor to the Spectrum Policy Task Force. In 2006 he was appointed Special Advisor to Mrs. Viviane Reding, European Commissioner for Information Society & Media. He is now Director of Marcus Spectrum Solutions LLC, an independent consulting firm based in the Washington DC area and focusing on wireless technology and policy. He is also Adjunct Professor of Electrical and Computer Engineering at Virginia Tech and the 2011-2013 chair of the IEEE-USA Committee on Communications Policy. He was recognized as a Fellow of the IEEE “for leadership in the development of spectrum management policies,” received in 1994 IEEE-USA’s first Electrotechnology Transfer Award, and received in 2013 the IEEE ComSoc Award for Public Service in the Field of Telecommunications "For pioneering spectrum policy initiatives that created modern unlicensed spectrum bands for applications that have changed our world."
In dynamic spectrum access (DSA) networks, one of the critical challenges in security and enforcement is to develop the mechanism to deter non-conforming transmitters that violate spectrum access rules prescribed by the regulatory authorities. One approach is to require every transmitter to embed a uniquely-identifiable authentication signal in its waveform at the PHY-layer. However, the design of the authentication signals proposed in the existing PHY-layer authentication schemes, pose a potentially serious threat to the privacy of the transmitters. Group signatures (GSs) is an elegant approach for providing privacy-preserving authentication. Unfortunately, modern GS schemes have limited practical value for use in DSA networks due to the high computational complexity of their revocation check procedures. We propose a novel GS scheme called the Group Signatures with Probabilistic Revocation (GSPR), which significantly improves scalability with regard to revocation. GSPR employs the novel notion of "alias codes", which enables the verifier to check the revocation status of the private key of a given signature very efficiently, but probabilistically. The motivation for using alias codes in GSPR comes from direct sequence spread spectrum (DSSS) systems used in 3G mobile communication. We discuss how the concepts related to spreading codes in DSSS are applied to design the revocation check procedure in GSPR. We show that GSPR makes an advantageous tradeoff between computational complexity and communication overhead, resulting in a GS scheme that offers a number of practical advantages over the prior art.
Bio: Vireshwar Kumar received his Bachelor's degree in Electrical Engineering from Indian Institute of Technology, Delhi, India in 2009. He worked at Dar Consultants in Pune, India as an Electrical Engineer before moving to Indian Institute of Science, Bangalore, India as a project assistant in 2010. Vireshwar joined the Department of Electrical and Computer Engineering at Virginia Tech, USA in 2011, and is currently a Ph.D. candidate. Vireshwar's research interests include security issues in wireless networks, and dynamic spectrum access networks.
As the demand placed on wireless networks continues to rapidly grow, devices must utilize available resources as efficiently as possible. Cognitive Radio (CR) provides an attractive solution to this problem, where devices learn from their experiences and make intelligent choices to optimize their own performance along with that of the network as a whole. Spectrum sharing is one particularly promising method that has gained a lot of interest as seen by the recent work in LTE-Unlicensed and by the federal government's plans to open a large portion of spectrum to the public for this very purpose. Research in this area is ongoing and many approaches have been proposed and studied.
While the theoretical concepts and algorithms related to this technology are being developed, it is important that an efficient test and evaluation methodology exist in order to bridge the gap from theory to practice. The Cognitive Radio Test System (CRTS) is a software framework being developed to facilitate rapid test and evaluation of cognitive radio networks. Development is taking place using the CORNET testbed at Virginia Tech, which consists of 48 Software-Defined Radio (SDR) nodes spread through a building on campus. A flexible and extensible base framework for CRTS has been developed and its initial capabilities demonstrated.
Deven Chheda graduated from the University of Mumbai, India with a Bachelor's degree in Electronics Engineering in 2007. He is currently in the second year of his Master's of Engineering program at Virginia Tech, and is advised by Dr. Vuk Marojevic. Prior to joining Virginia Tech, Deven has worked with the Indian Space Research Organization for about 7 years, participating in the development of antenna systems for space, air, and ground borne applications. His research interests include antenna systems, software defined radio technologies, and cellular communications systems, among others.
Raghunandan M Rao graduated from R.V. College of Engineering with a Bachelors degree in Telecommunication Engineering in 2011, and from the Indian Institute of Technology Kanpur with a Master of Technology in Photonics, in 2013. He joined the Bradley Department of Electrical and Computer Engineering in Fall 2014, and is currently pursuing his Master of Science degree in Electrical Engineering, advised by Dr. Vuk Marojevic. His research interests lie in the areas of Multi-antenna techniques, and Interference Mitigation in the LTE PHY Layer, among others.
Eric is an Masters student in MPRG advised by Dr. Michael Buehrer working on iterative receivers for MU-MIMO, and on several projects related to Software-Defined and Cognitive Radio with Dr. Carl Dietrich.
Dr. Howard Huang from Bell Labs, Murray Hill, NJ, is delivering a joint Bradley Distinguished Lecture and Wireless@VT seminar this Friday at 4pm in 190 Goodwin Hall (Quillen Family Auditorium).
Abstract: The deployment of Internet of Things (IoT) devices and services is accelerating, aided by ubiquitous wireless connectivity, declining communication costs, and the emergence of cloud platforms. Most major mobile network operators view the machine-to-machine (M2M) communication networks for supporting IoT as a significant source of new revenue. In this paper, we motivate the need for wide-area M2M wireless networks, especially for short data packet communication to support a very large number of IoT devices. We first present a brief overview of current and emerging physical and access-layer technologies for supporting wide area M2M. Then using communication theory principles, we discuss the fundamental challenges and potential solutions for these networks, highlighting tradeoffs and strategies for random and scheduled access.
Joint work with Harpreet Dhillon, Harish Viswanathan, and Andrea Biral.
Bio: Howard Huang received a B.S. in electrical engineering from Rice University in 1991 and a Ph.D. in electrical engineering from Princeton University in 1995. He has spent his entire career as a research engineer at Bell Labs, contributing to the fundamental understanding of multiple antenna (also known as multiple-input multiple-output, or MIMO) techniques and their application in cellular network standards including IS-95, UMTS, and LTE. He was a leading proponent of MIMO technologies in 3GPP UMTS standards, representing Bell Labs when MIMO was first proposed in 2000, and was a rapporteur for the MIMO work item. Dr. Huang has served as a guest editor on two issues of the IEEE Journal on Selected Areas of Communications focused on MIMO, and he is a co-author of the book MIMO Communication for Cellular Networks. Since 2013, he has led a group on Wireless Technologies for the Internet of Things which focuses on object tracking and machine-to-machine communications. Dr. Huang has taught as an adjunct professor at Columbia University and is a Fellow of the IEEE.
In spectrum sharing, a spatial separation region is defined around primary users (PUs) to protect them from secondary user (SU)-induced interference. This protection region-referred to by a number of names such as an exclusion zone (EZ) or a protection zone (PZ)-has a static boundary, and this boundary is determined conservatively to provide an additional margin of protection for the PUs. This legacy notion of interference protection is overly rigid, and often results in poor spectrum utilization efficiency.
In this paper, we propose a novel framework for prescribing interference protection for the PUs that addresses some of the limitations of legacy EZs. Specifically, we introduce the concept of Multi-tiered Incumbent Protection Zones (MIPZ), and show that it can be used to dynamically adjust the PU's protection boundary based on the radio environment, network conditions and the PU interference protection requirement. MIPZ can serve as an analytical framework for quantitatively analyzing a given PZ to gain insights on and determine the tradeoffs between interference protection and spectrum utilization efficiency. It allows a number of SUs, say N, to operate closer to the PU, and improves the overall spectrum utilization efficiency while ensuring a probabilistic guarantee of interference protection to the PU. We leverage the combined power of database-driven spectrum sharing and stochastic optimization theory for dynamically computing the zone boundary and the value of N. Using extensive simulation results, we demonstrate that the proposed framework adapts to the changing interference environment and improves spectrum utilization efficiency by adjusting the PU's PZ-boundary on the fly.
Bio: Sudeep Bhattarai is a Ph.D. student, working under Dr. Jerry Park, in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. He received his Bachelor's degree in Electronics and Communication Engineering from Institute of Engineering-Pulchowk Campus, Nepal in 2011, and Masters degree in Electrical Engineering from Tennessee State University in 2013. He was a research intern at University of Illinois-Urbana Champaign in summer 2013 and an intern at AT&T labs in summer 2014. Sudeep was the recipient of the best paper award in the technical track of IEEE DySPAN 2014. His current research interests include dynamic spectrum sharing, cognitive radio networks, adaptive beamforming and security issues in wireless communications.
Given the demands of global and pervasive connectivity, networks are becoming overly complex making them difficult to design, evolve, and manage. Analogous to the traditional network layering scheme, Software-Defined Networks (SDN) are based on the separation of control and data planes, creation of reusable components (i.e., abstraction and modularity), and virtualization. Continuing with the layered network view, the physical layer can be realized as a Software-Defined Radio (SDR). Both SDN and SDR share the concept of flexible provisioning for future communication networks.
The challenging demands of data services that are offered over different wireless access networks (e.g., WiFi, WiMax, GSM, CDMA, LTE, LTE-A, IoT, and WSN) and the success of SDN in wired networks motivates the extension of SDN to wireless networks. There are many related contributions in the literature, including OpenRadio, OpenRAN, SORA, OpenRoads, and H-CRAN.
There are two main approaches to leveraging SDN for wireless networks and integrating SDN with SDR. The first approach is to abstract the management and control operations of the access networks as software that is implemented in an SDN controller. This approach is most suitable for homogeneous wireless access networks. The second approach is to instantiate wireless resources, such as spectrum and equipment, and reallocate these resources as wireless virtual networks that meet customers' quality of service requirements and operators' capacity and coverage requirements. The latter is addressed as a wireless virtualization approach that applies the SDN network virtualization concept to wireless resources. Recently, wireless virtualization has garnered attention from both academia and industry. Such an approach presents many challenges.
This talk underlines the challenges and advances of using wireless virtualization in future heterogeneous wireless access networks. In particular, although SDR integration with SDN has been discussed in the literature, there is not a clear definition for such integration. This talk discusses how wireless virtualization may have the ability to bridge SDR to SDN. The talks will also discuss how this integration can contribute to the trade-off between flexibility and performance.
Emadeldin A. Mazied is a visiting scholar in the Bradley Department of Electrical Engineering at Virginia Tech. He has been a Ph.D. student in electrical engineering at Alexandria University, Egypt, since August 2014. He obtained his B.Sc. in Electronics Engineering from Menoufia University, Egypt, in 2003. He then worked as a technical engineer for the switching and networking department at the Informatics Institute, Alexandria, Egypt. He began his research in VoIP over wireless networks in 2010 at Alexandria University. He received the M.Sc. in Electrical Engineering from Alexandria University in June 2012. In July 2013 he received a research assistantship in the networking and distributed Systems department in the City for Scientific Research. In August. 2014, he received a scholarship for his Ph.D. studies at Alexandria University, including research at Virginia Tech. In October 2014 he received a teaching assistantship in the electrical Engineering department in Sohag University, Egypt. His research interests include wireless communication networks, QoS in future generation wireless networks, and SDN for wireless networks.
Abstract: Determining the locations of devices in mobile ad-hoc networks (MANETs), wireless sensor networks (WSNs), and cellular networks has many important applications. In MANETs, which are useful in disaster recovery, rescue operations, and military communications, location information is used to enable location-aided routing and geodesic packet forwarding. In WSNs, whose applications include environmental monitoring (e.g., for precision agriculture) and asset tracking in warehouses, not only is location information useful for the self-organization of the network, but in addition, tying locations to the sensor observations is crucial for adding meaning to the sensed data. In cellular networks, location information is used to provide subscribers with location-based services in addition to providing public service answering points with potentially life-saving location information during emergency calls. These applications are largely not new, which is evidenced by the fact that the literature is quite rich with localization studies presented over the span of many years. Because of this, it may be surprising to learn that there is a lack of analyses concerning the fundamental factors impacting localization performance.
Fundamentally, localization performance depends upon three factors: (i) the number of devices participating in the localization procedure, (ii) the locations of the participating devices, and (iii) the quality of the positioning observations gathered from the participating devices. For the most part, these factors cannot reasonably be considered deterministic. Instead, at any point in time, random effects within a network and its surroundings will determine these factors for individual positioning scenarios. Unfortunately, there are currently no analytical approaches for characterizing localization performance over these random factors. Instead, researchers either provide analytical results for a deterministic set of factors or use complex system-level simulations to obtain general performance insights. While the latter certainly averages over the random factors, the applicability of the results is limited by the simulation assumptions. Any change in a network parameter requires running a new time-consuming simulation.
In this seminar, I will present a new model for tractably analyzing network localization fundamentals, with a focus on its application to cellular positioning. After the model is presented, the model will be used to perform fundamental analyses of hearability and geometry. In addition to these specific results, another important result of our work is that we demonstrate to the localization community that there do, in fact, exist new tractable ways to analyze localization performance.
Bio: Javier Schloemann was born in San Jose, Costa Rica. He received a B.S. degree (with honors) in computer engineering in 2004 and an M.S. degree in electrical engineering in 2007, both from Clemson University, Clemson, SC, USA. After working for several years for Fluor Corporation as a process control systems and process automation engineer, he returned to academia and completed a Ph.D. degree in 2015 at Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA, with the Mobile and Portable Radio Research Group (MPRG) within Wireless@Virginia Tech. His current research interests include, among other things, classical and cooperative/collaborative positioning, Bayesian estimation and filtering, statistical signal processing, point process theory and stochastic geometry, as well as machine learning.
Abstract: What is the purpose of a wireless network? And how do we know if one is good? These are deceptively simple questions without good, simple answers. I begin by exploring these questions and discussing how we might make progress in answering them. We will see how even in the simple case of a single wireless link it can be difficult to adequately describe performance and that attempts to do so are application dependent and usually invoke stochastic notions. We will also discuss properties of measures of social welfare and see tradeoffs that arise between fairness and utilitarianism. Having thus set the stage, we use this perspective to examine emerging technologies, the impact that they could have on wireless networks, and the particular challenges that they pose. In particular, I first consider the potential role of wireless network virtualization in enabling the orchestration of fit-for-purpose wireless networks and show some preliminary results on the ability of virtualization to reduce cost and improve user satisfaction. Then, I consider the implications of millimeter wave technology for future wireless network design. Although millimeter wave technology offers promises of blinding speed and access to wide open spectrum, link impediments may make it difficult to realize these benefits in ways that benefit users without significant changes to the rest of the protocol stack. Finally, we briefly examine some of the analytical tools, including game theory, stochastic optimization, and stochastic geometry, that may help us to design and understand future wireless networks.
Allen B. MacKenzie received his bachelor's degree in Electrical Engineering and Mathematics from Vanderbilt University in 1999. In 2003 he earned his Ph.D. in electrical engineering at Cornell University and joined the faculty of the Bradley Department of Electrical and Computer Engineering at Virginia Tech, where he is now an associate professor. During the 2012-2013 academic year, he was an E.T.S. Walton Visiting Professor at CTVR: The Telecommunications Research Centre at Trinity College Dublin. Prof. MacKenzie's research focuses on wireless communications systems and networks. His research interests include cognitive radio and cognitive network algorithms, architectures, and protocols and the analysis of such systems and networks using game theory. His past and current research sponsors include the National Science Foundation, Science Foundation Ireland, the US Army, the Defense Advanced Research Projects Agency, and the National Institute of Justice. Prof. MacKenzie is an associate editor of the IEEE Transactions on Cognitive Communications and Networking and the IEEE Transactions on Mobile Computing and an area editor of the IEEE Transactions on Communications. He also serves on the technical program committee of several international conferences in the areas of communications and networking, and is a regular reviewer for journals in these areas. Prof. MacKenzie is a senior member of the IEEE and a member of the ASEE and the ACM. He is the author of more than 50 refereed conference and journal papers and the co-author of the book Game Theory for Wireless Engineers. Dr. MacKenzie is also the Associate Director of the Wireless @ Virginia Tech research group.