Date: December 6, 2019
Title: Implementation Considerations in Dynamic Spectrum Access (DSA) Systems
Speaker: Ihsan Akbar, Shared Spectrum Company
Abstract: Dynamic Spectrum Access (DSA) technology is currently one of the most widely studied research areas in wireless communications. It will change the fundamentals of how wireless systems work in real world. However, there are still open areas for research in implementing and deploying DSA systems. Shared Spectrum Company has extensive experience in DSA and has conducted several programs that focus on this technology. This talk will cover practical aspects and challenges of implementing DSA solutions in real world wireless systems.
Bio: Dr. Akbar received his Masters and Ph.D. from Virginia Tech in 2002 and 2007 respectively. His research interests are in the area of Dynamic Spectrum Access, Markov Modeling, Digital Signal Processing, and Communications Theory. He is currently serving as an Adjunct Research Professor at the Bradley Department of Electrical and Computer Engineering at Virginia Tech. Earlier, Dr. Akbar has also served as the Co-chair of Cognitive Radio Working Group (CRWG) at Wireless Innovation Forum (WinnForum). Dr. Akbar is currently working as a Principal Engineer at Shared Spectrum Company where he leads several US Gov’t funded research projects.
Date: November 1, 2019
Title: Coping Uncertainty in Coexistence via Exploitation of Interference Threshold Violation
Speaker: Shaoran Li, Wireless@VT
Abstract: In underlay coexistence, secondary users (SUs) attempt to keep their interference to primary users (PUs) under a threshold. Due to the absence of cooperation from the PUs, there exists much uncertainty at the SUs in terms of channel state information (CSI). In this talk, I will introduce a relatively new approach called chance-constrained programming (CCP) to address channel uncertainty where only the mean and covariance of the interference channel gains are available. Our work relies on the idea that occasional interference threshold violation is acceptable as long as such threshold violation happens below a given probability (usually called risk level). To tackle the intractable CCP formulation, we introduce a novel mathematical technique called Exact Conic Reformulation (ECR) that reformulates the original problem into a tractable deterministic optimization problem. We show that our proposed solution predicated on ECR offers better performance and is applicable in more general settings, which successfully overcomes the limitations associated with the state-of-the-art approach.
Bio: Shaoran Li is a Ph.D. candidate in the Bradley Department of Electrical and Computer Engineering at Virginia Tech since Fall 2017. He received his B.S. degree from Southeast University (SEU), Nanjing, China, in 2014 and M.S. degree from Beijing University of Posts and Telecommunications (BUPT), Beijing, China in 2017. His current research interests include algorithm design and implementation in the wireless networking area, especially associated with uncertainty.
Date: October 11, 2019
Title: Robust SINR Estimation and Dual CSI Feedback for Pulsed Radar-Cellular Spectrum Sharing Scenarios
Speaker: Raghunandan Rao, Wireless@VT
Abstract: Accurate channel state information (CSI) is crucial to maximize the link performance of a wireless system. In practice, it is the key input to various PHY and MAC blocks such as link adaptation, beamforming, scheduling etc. In modern cellular systems, quantized CSI (such as SINR, channel rank, and precoding) is acquired by a training stage using reference/pilot symbols. In this talk, we discuss how structured 'non-pilot interference' (NPI) waveforms distort pilot-aided CSI estimates, resulting in degradation of throughput and latency performance. Unfortunately, pulsed radar waveforms fall under this category, which can be a bottleneck for pilot-aided CSI acquisition in radar-cellular spectrum sharing scenarios. In order to mitigate this, we propose a max-min heuristic to estimate the SINR of the contaminated OFDM symbol blindly, and give a mathematical justification for its "probabilistically robust" estimation performance. We then integrate this heuristic into a processing pipeline of semi-blind SINR estimation and dual-CSI feedback. Through link-level simulations using the LTE/LTE-A/LTE-A Pro downlink as an example, this framework is shown to significantly outperform conventional CSI estimation and feedback techniques in pulsed radar-cellular spectrum sharing scenarios.
Bio: Raghunandan M. Rao is a Ph.D. Candidate in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, affiliated with the Wireless@VT research group since Summer 2015. He obtained his M.S. in Electrical Engineering from Virginia Tech in 2016, and M.Tech. in Laser Technology from the Indian Institute of Technology, Kanpur in 2013. In the past, he has held summer internships at Blue Danube Systems, MACOM, and Samsung Research America. His current research interests include spectrum sharing, massive MIMO, localization, and stochastic geometry.
Date: September 27, 2019
Title: A Diverse Band-aware Dynamic Spectrum Access (d-DSA) Network Architecture for Ubiquitous Rural Connectivity
Speaker: Vijay Shah, Wireless@VT
Abstract: Ubiquitous connectivity plays an important role in improving the quality of life in terms of economic development, health and wellbeing, to name a few. However, rural communities which account for 46% of the world's population lacks access to proper connectivity to avail such societal benefits, creating a huge “digital divide" between the urban and rural areas. A primary reason is that the Information and Communication Technologies providers have less incentives to invest in rural areas due to lack of promising revenue returns. Existing research and industrial attempts suffer from severe drawbacks, such as expensive wireless spectrum licenses and infrastructures, under- and over-provisioning of spectrum resources while handling heterogeneous network traffic etc.
Leveraging the recent advances in Dynamic Spectrum Access (DSA) technologies like wide band spectrum analyzers and spectrum access systems, and multi-radio access technologies (multi-RAT), this presentation discusses a novel Diverse Band-aware DSA (d-DSA) network architecture, that addresses the drawbacks of existing standard and DSA wireless solutions, and extends ubiquitous connectivity to rural communities; a step forward in the direction of the societal and economic improvements in rural communities, and hence, narrowing the "digital divide" between the rural and urban societies. According to this paradigm, a certain wireless device is equipped with software defined radios (SDRs) that are capable of accessing multiple (un)licensed spectrum bands, such as, TV, LTE, GSM, CBRS, ISM, and possibly futuristic mmWaves. In order to fully exploit the potential of the d-DSA paradigm, while meeting heterogeneous traffic demands that may be generated in rural communities, we design efficient routing strategies and optimization techniques, which are based on a variety of tools such as graph modeling, integer linear programming, dynamic programming, and heuristic design. Our results on realistic traces in a large variety of rural scenarios show that the proposed techniques are able to meet the heterogeneous traffic requirements of rural applications, while ensuring energy efficiency and robustness of the architecture for providing connectivity to rural communities.
Bio: Vijay is a Research Assistant Professor in Wireless@VT, Bradley Department of Electrical and Computer Engineering at Virginia Tech. He received his PhD degree in Computer Science from University of Kentucky in 2019, and B. Tech degree in Computer Science and Engineering from National Institute of Technology, Durgapur, India in 2013. His research interests include Wireless networks, Spectrum sharing, Graph modeling, Optimization techniques, Cross-layer network design, and 5G networks. He has published several research papers in top-tier networking conferences and journals, such as, ACM TOSN, IEEE TMC, IEEE TMBMC, IEEE INFOCOM, ACM BuildSys etc, and is a recipient of notable accolades, including, 2019 Outstanding CS Graduate Student Award by College of Engineering at University of Kentucky, three best poster awards, and several ACM/IEEE travel grant awards.
Date: September 20, 2019
Title: Performance Characterization of Canonical Mobility Models in Drone Cellular Networks
Speaker: Morteza Banagar, Wireless@VT
Abstract: In this talk, we characterize the performance of several canonical mobility models in a drone cellular network in which drone base stations (DBSs) serve user equipments (UEs) on the ground. In particular, we consider the following four mobility models: (i) straight line (SL), (ii) random stop (RS), (iii) random walk (RW), and (iv) random waypoint (RWP), among which the SL mobility model is inspired by the simulation models used by the third generation partnership project (3GPP) for the placement and trajectory of drones, while the other three are well-known canonical models (or their variants) that offer a useful balance between realism and tractability. Assuming the nearest-neighbor association policy, we consider two service models for the UEs: (i) UE independent model (UIM), and (ii) UE dependent model (UDM). While the serving DBS follows the same mobility model as the other DBSs in the UIM, it is assumed to fly towards the UE of interest in the UDM and hover above its location after reaching there. Our main contribution is to present a unified approach to characterize the point process of DBSs for all the mobility and service models. Using this, we provide exact mathematical expressions for the average received rate and the session rate as seen by the typical UE. Further, using tools from calculus of variations, we concretely demonstrate that the simple SL mobility model provides a lower bound on the performance of other general mobility models (including the ones in which drones follow curved trajectories) as long as the movement of each drone in these models is independent and identically distributed (i.i.d.). This talk provides a rigorous analysis of key canonical mobility models for an infinite drone cellular network and establishes useful connections between them.
Bio: Morteza Banagar is a Ph.D. student in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. He received his B.Sc. and M.Sc. degrees in Communications Engineering from the University of Tehran, Iran, in 2012 and 2014, respectively. His current research interests include UAV/drone communications, stochastic geometry, and wireless communications.
Date: April 26, 2019
Speaker: Paul Petrus, Ruckus Networks
Title: "Citizen Broadband Radio Service (CBRS) Fundamentals & Applications"
Abstract: Citizens Broadband Radio Service (CBRS) is a 150MHz wide spectrum in the 3.5GHz band (3550 MHz to 3700 MHz) available only in the US. In 2017, the FCC completed a process begun in 2012 to establish rules for commercial use of this band. A small segment of this spectrum is currently occupied by United States Navy radar systems and Fixed Satellite Services (FSS), aka incumbents. Commercial applications will be available where the incumbents are not present and the band will be available for commercial use in 2019.
Wireless Service Providers using CBRS will be able to deploy 4G & 5G mobile networks without having to acquire expensive spectrum licenses. CBRS is governed by a three-tiered spectrum authorization framework to accommodate a variety of commercial uses on a shared basis with incumbent users of the band. Access and operations will be managed by a Spectrum Allocation Server (SAS), conceptually similar to the databases used to manage Television White Spaces devices. The three tiers are: Incumbent Access, Priority Access, and General Authorized Access.
This talk will focus on the history, fundamentals and industry applications of CBRS. CBRS networks need to be deployed in a coordinated fashion and coexistence between the networks is important for the success of this band. This talk will highlight the interference challenges and possible solutions.
Bio: Dr. Paul Petrus is a Vice President of Engineering at Ruckus Networks, leading the CBRS Small Cells product development. Paul joined Ruckus in 2014 to start this new product line. Ruckus is a leading developer of wireless and wired products (WiFi AP, CBRS-LTE AP and Switches) for Enterprises like Hotels, Universities and K-12 schools.
Prior to joining Ruckus, Paul was a Sr. Director of Technology at Qualcomm. At Qualcomm, Paul lead the development of next generation 11ac WiFi mobile chipset. Prior to this, Paul was the engineering lead for Internet of Things (IoT) initiative at Qualcomm, focusing on low power technologies that went into Xbox360 in 2013. Paul came into Qualcomm through the acquisition of Atheros Communications, where he was the Director of Architecture. At Atheros, he oversaw the development of four generations of WiFi chips.
Paul received his Doctorate degree in Electrical Engineering from Virginia Tech in 1997. He has authored/co-authored more than 20 IEEE Journal and Conference papers. He is also an inventor/co-inventor of 30 US/International patents.
Date: April 5, 2019
Speaker: Tim O'Shea, Hume Center
Title: "Learning from Data in Radio Signal Processing: Leveraging machine learning to tackle real world complexity"
Abstract: Communications systems face a wide range of impairments and propagation effects and have continued to increase rapidly in system and algorithmic complexity as dense, multi-user, multi-antenna, dynamic systems share spectrum over a wide range of application and performance requirements while our tools for jointly optimizing such systems under real world conditions and assumptions has not kept pace. Meanwhile over the past decade, deep learning has revolutionized fields such as computer vision and natural language processing, by redefining the state of the art in numerous algorithmic tasks by expressing objective functions concisely and globally and relying on powerful learning algorithms, computation and architectures to perform end-to-end learning and feature learning on rich, high dimension real world datasets and distributions which cannot be easily reduced to compact analytic forms. These same techniques hold enormous promise for the future of radio sensing and communications systems, allowing for systems and algorithms which may be synthesized and optimized in an end-to-end fashion, exploiting data and experience more fully throughout the signal processing chain, without making rigid assumptions or simplifying conditions. Such a data-driven approach to the design of radio signal processing systems has begun to receive significant increased attention throughout IEEE ComSoc and the wider industry over the past several years, and at this point seems somewhat of an inevitable direction for the field as it has been in other fields, and as quantitative research continues to demonstrate results. This talk will introduce how basic problems of communications and radio signal processing can be formulated as high-level end-to-end machine learning problems, review recent work in the field, and explore the wide-open field of opportunity that exist right now in terms of open research and development opportunities within this new way of approaching numerous emerging and classical wireless problems.
Bio: Dr. Tim O’Shea is a Research Assistant Professor at Virginia Tech’s Hume Center for National Security and Technology in Arlington where he is focused on applied research in the area of machine learning and data driven synthesis of signal processing systems in wireless communications, information security, and design. He has led research programs including for NSF, NASA, DARPA, DOD, and industry, has published over 50 peer reviewed articles in the field, serves as co-chair for IEEE Machine Learning for Communications emerging technology initiative and on the editorial board for the IEEE Transactions on Wireless Communications and IEEE Transactions on Cognitive Communications and Networking. He is also a co-founder and CTO of DeepSig which is focused on enhancing 5G and other wireless communications systems using machine learning to enhance software & algorithms, and the inventor of a number of patents in the area.
Date: March 18, 2019
Speaker: Charles A. Kamhoua, U.S. Army Research Laboratory (ARL)
Title: "Game theoretic modeling of cyber deception in the Internet of Battlefield Things"
Abstract: Most sophisticated cyber attack follow the well-known cyber kill chain. The first step of the cyber kill chain is the reconnaissance phase where attacker probe the network in search of weakness, misconfiguration, vulnerabilities, and identify potential targets before the actual attack start. To this end, the attacker need to collect important information about the characteristics of each devices (i.e., hardware, operating system, applications), the network topology, the different subnet, firewall rules, access control, privilege, the communication protocol at each layer, and the machine learning algorithm on each IoBT devices. The attacker reconnaissance can be summarized by an attack graph in which the node represent vulnerable IoBT devices and the edge show their associated vulnerabilities.
This work investigates cyber deception as a complex game in which each player has three concurrent and interdependent objectives. Each players imperfectly monitor (partial observation) other players’ action to find out each player’s identity, strategies, payoff, available information, capability, and to continuously predict their intent. Each player strategically select to which players to hide particular information (e.g., camouflage). Each player judiciously manipulate other players’ perception (e.g., decoy) based on his observed action, estimated capability, and predicted intent. This work examines from the defender’s perspective several deception game on an attack graph. The defender goal is to stop the attacker early in the cyber kill chain and prevents the subsequent more dangerous phases.
Bio: Charles A. Kamhoua is a researcher at the Network Security Branch of the U.S. Army Research Laboratory (ARL) in Adelphi, MD, where he is responsible for conducting and directing basic research in the area of game theory applied to cyber security. Prior to joining the Army Research Laboratory, he was a researcher at the U.S. Air Force Research Laboratory (AFRL), Rome, New York for 6 years and an educator in different academic institutions for more than 10 years. He has held visiting research positions at the University of Oxford and Harvard University. He has co-authored more than 150 peer-reviewed journal and conference papers. He is a co-inventor of 2 patents and 5 patent applications. He has been at the forefront of several new technologies, co-editing three books at Wiley-IEEE Press entitled "Assured Cloud Computing", "Blockchain for Distributed System Security" and "Modeling and Design of Secure Internet of Things", forthcoming. He has presented over 50 invited keynote and distinguished speeches and has co-organized over 10 conferences and workshops. He has mentored more than 60 young scholars, including students, postdocs, and Summer Faculty Fellow. He has been recognized for his scholarship and leadership with numerous prestigious awards, including the 2019 Federal 100-FCW annual awards for individuals that have had an exceptional impact on federal IT, the 2018 ARL Achievement Award for leadership and outstanding contribution to the ARL Cyber Camo (cyber deception) project, the 2018 Fulbright Senior Specialist Fellowship, the 2017 AFRL Information Directorate Basic Research Award “For Outstanding Achievements in Basic Research,” the 2017 Fred I. Diamond Award for the best paper published at AFRL’s Information Directorate, 40 Air Force Notable Achievement Awards, the 2016 FIU Charles E. Perry Young Alumni Visionary Award, the 2015 Black Engineer of the Year Award (BEYA), the 2015 NSBE Golden Torch Award—Pioneer of the Year, and selection to the 2015 Heidelberg Laureate Forum, to name a few. He has been congratulated by the White House, the US Congress and the Pentagon for those achievements. He received a B.S. in electronics from the University of Douala (ENSET), Cameroon, in 1999, an M.S. in Telecommunication and Networking from Florida International University (FIU) in 2008, and a Ph.D. in Electrical Engineering from FIU in 2011. He is currently an advisor for the National Research Council postdoc program, a member of the FIU alumni association and ACM, and a senior member of IEEE.
Date: March 8, 2019
Speaker: Parker White, Hume Center at Virginia Tech
Title: "Blind Frequency Hopping Spread Spectrum Source Separation with Constrained Clustering"
Abstract: Frequency Hopping Spread Spectrum (FHSS) communication is a digital communication technique commonly used for its narrow band interference resistance as well as its low probability of detection. For this reason, FHSS is typically preferred when narrow-band interference is highly probable, or unintended listeners with the intention of jamming may be present. In either case, if a consistent problem interferer is present, the identification of this interferer is crucial for threat analysis and communication link integrity. As machine learning aided spectrum sensing techniques improve, the detection and estimation of frequency hopping characteristic parameters can be used to distinguish signal sources and identify a consistent problem interferer. Classical distance based clustering is a common technique in grouping a set of objects based on the similarity of their parameter sets. However, this technique does not account for any background knowledge that may be present in the problem scenario. Utilizing background knowledge in the form of instance level pairwise constraints can improve clustering performance in the application of frequency hopping signal separation.
Bio: Parker White is currently working on a Master of Science in electrical engineering under Dr. Buehrer and Dr. Headley. He received his undergraduate degree from West Virginia University with an emphasis in communications and signal processing. Parker plans on graduating late summer of this year.
Date: March 1, 2019
Speaker: Brad Brannon, Analog Devices
Title: "Challenges and Advancements in Next Generation Integrated Radio Technology"
Abstract: Radio recently celebrated its 100th anniversary and yet it continues to evolve and change the way it impacts our daily lives. For much of the last hundred years those architectures remained unchanged, yet in the last few years, the pace of evolution has increased as semiconductor technology removes old barriers and enable new topologies. What obstacles has radio overcome in the past and what bumps exist in the road ahead? What might the future of radio look like in the coming years?
Bio: Brad Brannon is a system architect and has worked at Analog Devices for 35 years following his graduation from North Carolina State University. At ADI he has held positions in design, test, applications, and in system engineering. Brad has authored a number of articles and application notes on topics that span clocking data converters, designing radios, and testing ADCs. Currently Brad is responsible for system engineering for 4G and 5G radio architectures.
Date: February 8, 2019
Speaker: Joel Kees, Virginia Tech
Title: "Robust Blind Spectral Estimation in the Presence of Impulsive Noise"
Abstract: Robust nonparametric spectral estimation involves generating an accurate estimate of the Power Spectral Density (PSD) for a given set of data while trying to minimize the bias due to data outliers. This is applied in the domain of electrical communications and digital signal processing when a PSD estimate of the electromagnetic spectrum is desired (often for the goal of signal detection), and when the spectrum is also contaminated by Impulsive Noise (IN). Power Line Communication (PLC) is an example of a communication environment where IN is a concern because power lines were not designed with the intent to transmit communication signals. There are many different noise models used to statistically model different types of IN, but one popular model that has been used for PLC and various other applications is called the Middleton Class A model, and this model is extensively used in this thesis. The performance of two different nonparametric spectral estimation methods are analyzed in IN: the Welch method and the multitaper method. These estimators work well under the common assumption that the receiver noise is characterized by Additive White Gaussian Noise (AWGN). However, the performance degrades for both of these estimators when they are used for signal detection in IN environments. In this thesis, basic robust estimation theory is used to modify the Welch and multitaper methods in order to increase their robustness.
Bio: Joel Kees is graduating with a Master of Science in electrical engineering under Dr. Beex. He received his undergraduate degree from Virginia Tech. In the spring, he will begin working full-time for LGS innovations in Northern Virginia. In his free time, he likes to read and mountain unicycle.
Date: February 1, 2019
Speaker: Dr. Charles Clancy, Virginia Tech Hume Center
Title: Security and Privacy for the 5G Core Network
Abstract: 5G introduces many new features, including new Radio Access Network (RAN) protocols to support higher data rates. However, many of the exciting new features of 5G are within the core network. Completely re-envisioned as a microservices architecture that can be elastically deployed within a cloud environment, 5G goes head-first into the world of Software-Defined Networking (SDN) enabled by Network Function Virtualization (NFV). Using this toolbox, 5G introduces the concept of network slicing which allows vertical integration of networking services with the cloud and the ability to elastically deploy services. This talk will provide a tutorial of these new features within 5G, with a specific focus on security and privacy issues associated with them.
Bio: Dr. Charles Clancy is the Executive Director of Virginia Tech's Hume Center for National Security and Technology and is the Bradley Professor of Electrical and Computer Engineering. With 85 faculty and staff, the Hume Center engages over 400 students annually in research and experimental learning focused in national security and technology. Dr. Clancy is an internationally-recognized expert at the intersection of wireless, cybersecurity, and artificial intelligence.
Prior to joining Virginia Tech in 2010, he served as a researcher at the National Security Agency. Dr. Clancy received his BS in Computer Engineering from the Rose-Hulman Institute of Technology, MS in Electrical Engineering from the University of Illinois, and PhD in Computer Science from the University of Maryland. He is a Senior Member of the IEEE and has over 200 peer-reviewed technical publications and patents, is co-author to five books, and co-founder to four venture-backed startup companies.