NEWSDR 2024 – Boston Software Defined Radio User Group

14th New England Workshop on Software-Defined Radio

Innovation Studio, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA, USA
Main Event: Friday 31 May 2024, 9:00 AM (US Eastern) – 5:00 PM (US Eastern)
Tutorials: Thursday 30 May 2024, 5:00 PM (US Eastern) – 9:00 PM (US Eastern)

The 2024 New England Workshop on Software-Defined Radio (NEWSDR’24) is the fourteenth installment of an annual workshop series organized by the Boston SDR User Group (SDR-Boston). We are very excited about this year’s NEWSDR event being hosted in-person on the beautiful campus of Worcester Polytechnic Institute (WPI) in Worcester, MA, USA. The primary goal of this workshop is to provide a forum that enables SDR enthusiasts to get together, collaborate, and introduce SDR concepts to those interested in furthering their knowledge of SDR capabilities and available resources. NEWSDR 2024 welcomes both experienced SDR enthusiasts as well as individuals who are interested in getting started with SDR.

This website will continue to be updated as the event evolves, so please visit frequently for the latest information about NEWSDR 2024!

NEWSDR 2024 Attendees Group Photo

Photo Credit: Nancy Kotary

Workshop Registration

Online registration for this event is closed. On site registration will be available the day of the event but with no guarantee of lunch, parking, and other services.

Latest Agenda

NEWSDR 2024 activities are distributed over Thursday 30th (evening tutorials) and Friday 31st (main event) on the first and second floors of the WPI Innovation Studio (see map below).

Thursday 30 May 2024 — Evening Session
(Rooms IS105, IS203, IS205, IS207)

05:00pm – 06:00pm EDT	*Networking Session* (with Pizza) Innovation Studio, 2nd Floor Diamond Lounge Area
06:00pm – 09:00pm EDT	*Sponsor Tutorial: Mathworks “Hands-On Satellite Communications Workshop“* Room IS105
06:00pm – 09:00pm EDT	*Sponsor Tutorial: PI-Radio “How to Build an FR3 SDR“* Room IS203
06:00pm – 09:00pm EDT	*Sponsor Tutorial: TMYTEK “mmW-OAI: An FR2-enabled OAI Testbed*“ Room IS205
06:00pm – 09:00pm EDT	*Sponsor Tutorial: NI “FPGA Programming on the USRP with the RFNoC Framework*“ Room IS207

Friday 31 May 2024 — Morning Session
(Room IS203/IS205)

09:00am – 09:15am EDT	*Welcome Address and Event Overview* NEWSDR Organizing Committee
09:15am – 10:00am EDT	*Opening Talk**: Taejoon Kim (University of Kansas), Vuk Marojevic (Mississippi State University) “Zero Trust X (ZTX): Operating Securely Through 5G Infrastructure“*
10:00am – 10:30am EDT	*Sponsor Talks*: Mathworks (Mike Mclernon) MITRE (Ken Schmitt) Pi-Radio (Aditya Dhananjay) TMYTEK (Toabis Huang) NI (Neel Pandeya)
10:30am – 11:10am EDT	*Spotlight Talks/*Poster Preview Session (Titles & Abstracts)
11:10am – 11:30am EDT	*Networking Session* (with coffee)
11:30am – 12:15pm EDT	*Invited Talk: Michele Polese (Northeastern University) “Accelerating End-to-End AI/ML Design for Open RAN with Colosseum as a Digital Twin“*

Lunch will be served during 12:15pm – 1:15pm EDT in Innovation Studio, 2nd Floor Diamond Lounge Area (priority access given to online registrants)

Friday 31 May 2024 — Afternoon Session
(Room IS203/IS205)

01:15pm – 01:45pm EDT	Invited Talk: Ken Schmitt (MITRE) “Extremely Wideband RF Spectrum Operations“
01:45pm – 02:45pm EDT	*Keynote Fireside Chat:* Speaker: Matt Ettus Moderator: Alexander Wyglinski (WPI) “20 Years of SDR Innovation: How Far We’ve Traveled and Where We’re Going“
02:45pm – 03:00pm EDT	Networking Session (with coffee)
03:00pm – 03:45pm EDT	Graduating PhD Student Talks: Adriyel Nieves (WPI) “RF Fingerprinting Testbed and Classification Experiments“ Kat Kononov (MIT) “Synthesis Imaging with Vector Sensor Arrays“ Gerald LaMountain (Northeastern University) “Adaptive and Robust Tracking and Acquisition on a software-defined open-source GNSS receiver“
03:45pm – 04:30pm EDT	Invited Talk: John Swoboda and Ryan Volz (MIT Haystack Observatory) “Space Weather Monitoring with Novel Radar Systems: The 2024 Eclipse“
04:30pm – 04:40pm EDT	Closing Ceremony NEWSDR Organizing Committee

On-Campus Parking

Online registrants were sent earlier this week a visitor parking pass that must be clearly displayed on the dashboard of the vehicle (any other vehicle without a visitor parking pass or the pass is not clearly presented will be ticketed). All attendees should park in the main parking area (not the visitor parking spots) of the Park Avenue garage located at 151 Salisbury St, Worcester, MA (see map below).

Presentation Information

Keynote Fireside Chat: 20 Years of SDR Innovation: How Far We’ve Traveled and Where We’re Going

Abstract: Software defined radio technology has dramatically evolved over the past 20 years from simple platforms generating narrowband transmissions and limited functionality to wideband communication systems capable of producing sophisticated wireless waveforms that are standards-compliant and employing the latest in digital communications and signal processing algorithms such as MIMO, beamforming, OFDM, and AI-based implementations. With innovations achieved across all aspects of the SDR ecosystem, including the computing hardware, radio frequency front-end, software development environment, and algorithmic support, the potential of SDR has completely revolutionize how we research and develop communications and networking solutions, enabling greater accessibility both in terms of radio functionality as well as useability by the general wireless community. However, have we reached the full potential of SDR? Or is there more that awaits us in terms of the capabilities of this transformative technology? Join us for this exciting fireside chat with one of the wireless industry’s most influential innovators who helped fuel this revolution in wireless communication systems prototyping and experimentation.

Keynote Presenter: Matt Ettus is the creator of the Universal Software Radio Peripheral (USRP) series of software defined radio products and was a core contributor to the GNU Radio project, a free framework for software radio. In 2004, he founded Ettus Research to develop, support, and commercialize the USRP; this revolutionary platform is currently used in over 100 countries worldwide across a wide range of applications including 5G, radio astronomy, satellite communications, medical imaging, and wildlife tracking. In 2010, National Instruments acquired Ettus Research, with Matt subsequently serving as its Distinguished Engineer. That same year, the USRP family won the Technology of the Year award from the Wireless Innovation Forum. Matt joined Apple in 2017, where he is a Distinguished Engineer and serves as a Technical Leader and co-founder of Satellite Connectivity Group which developed the new SOS over Satellite system for iPhone. Matt received his B.S.E.E. and B.S.C.S. degrees from Washington University, and an M.S.E.C.E. degree from Carnegie-Mellon University. In 2011, Matt was named an eminent member of Eta Kappa Nu, and in 2024 he was elevated to the grade of IEEE Fellow. Matt is based in Silicon Valley.

Moderator: Alexander Wyglinski is the Associate Dean of Graduate Studies, a Professor of Electrical Engineering and Robotics Engineering, and Director of the Wireless Innovation Laboratory at Worcester Polytechnic Institute (WPI), Worcester, Mass, USA. Dr. Wyglinski served as President of the IEEE Vehicular Technology Society (2018-2019), and is the co-founder of the NEWSDR workshop series of events. He received his B.Eng. and Ph.D. degrees in Electrical Engineering from McGill University, Montreal, Canada in 1999 and 2005, and his M.Sc.(Eng.) degree in Electrical Engineering from Queen’s University, Kingston, Canada in 2000. Dr. Wyglinski’s current research interests are in wireless communications, cognitive radio, machine learning for wireless systems, software defined radio prototyping, connected and autonomous vehicles, and dynamic spectrum sensing, characterization, and access.

Accelerating End-to-End AI/ML Design for Open RAN with Colosseum as a Digital Twin

Abstract: In this talk, I will discuss how openness, programmability, and intelligence (key components of the Open Radio Access Network, or Open RAN, vision) can restart the innovation cycle in mobile networks. I will focus specifically on how we can address one of the major challenges in the design of intelligent Open RAN systems, i.e., the design of artificial intelligence and machine learning solutions that are effective, scalable, and can generalize well across deployment scenarios and conditions. I will discuss how we leveraged Colosseum – the world’s largest wireless network emulator with hardware in the loop – as a digital twin for Open RAN systems, to (i) collect large-scale datasets in a variety of representative scenarios; (ii) test and profile agile and AI-driven RAN control in a safe environment with the OpenRAN Gym framework; (iii) how we developed and tested explainable AI solutions (EXPLORA) for Open RAN in Colosseum; and (iv) how we used Colosseum to evaluate solutions for real-time control of the RAN (dApps).

Presenter: Michele Polese is a Research Assistant Professor at the Institute for the Wireless Internet of Things, Northeastern University, Boston, since October 2023. He received his Ph.D. at the Department of Information Engineering of the University of Padova in 2020. He then joined Northeastern University as a research scientist and part-time lecturer in 2020. During his Ph.D., he visited New York University (NYU), AT&T Labs in Bedminster, NJ, and Northeastern University.
His research interests are in the design and testing of next-generation wireless networks, 5G/6G, and Open RAN, in open, intelligent, and programmable end-to-end network architectures, and in open-source networking software and experimental wireless testbeds. He has contributed to O-RAN technical specifications and submitted responses to multiple FCC and NTIA notices of inquiry and requests for comments, and is a member of the Committee on Radio Frequency Allocations of the American Meteorological Society. He is PI and co-PI in research projects on 6G funded by the O-RAN ALLIANCE and the U.S. NSF, OUSD, and NTIA, and was awarded with several best paper awards and the 2022 Mario Gerla Award for Research in Computer Science. Michele served as TPC co-chair for WONS 2024, ACM WiNTECH 2023, WNS3 2021-2022, as an Associate Technical Editor for the IEEE Communications Magazine, as a Guest Editor in an IEEE JSAC Special Issue on Open RAN, and has organized the Open 5G Forum in Fall 2021 and the NextGenRAN workshop at Globecom 2022.

Zero Trust X (ZTX): Operating Securely Through 5G Infrastructure

Abstract: The emergence of high-performance 5G networks presents a potential paradigm shift for secure military communications. However, commercially available 5G equipment often lacks robust security protocols, rendering sensitive data vulnerable to unauthorized access and manipulation. ZTX addresses this challenge by developing innovative security solutions without changing existing 5G standards. This talk outlines the ZTX security framework, empowering DoD operators to implement layered security measures on their devices, achieving independence from potentially compromised network infrastructure. ZTX also incorporates network-centric security solutions for comprehensive protection. This talk then presents how ZTX uses open-source software and software radio testbeds to implement and demonstrate secure communications over 5G RAN and O-RAN testbeds and showcase our parallel development and demonstration efforts that use commercial 5G user devices and networks as the testbed.

Presenters: Taejoon Kim is an Associate and Chair’s Council Professor of the Electrical Engineering and Computer Science (EECS) Department at the University of Kansas (KU), where he researches 6G networked systems, security, distributed learning, and information theory. He leads seven active NSF projects as a PI or Co-PI. He has received numerous awards, including the KU School of Engineering Research Excellence Award (Miller Professional Award for Research), the Harry Talley Excellence in Teaching Award, the IEEE Transactions on Communications Best Paper Award (Stephen O. Rice Prize), and the IEEE PIMRC Best Paper Award. He was an associate editor of the IEEE Transactions on Communications. He earned his Ph.D. in ECE from Purdue University and held positions at Nokia Bell Labs, KTH Royal Institute of Technology, and the City University of Hong Kong.

Vuk Marojevic, an Associate Professor of Electrical and Computer Engineering at Mississippi State University. He graduated from the University of Hannover, Germany, and Barcelona Tech (UPC), Spain, with an MS and Ph.D. in Electrical Engineering. He leads research in mobile communications, software-defined radios, and wireless security, with a focus on mission-critical applications and O-RAN. He is an associate editor of the IEEE Transactions on Vehicular Technology and the IEEE Vehicular Technology Magazine. Dr. Marojevic is a principal investigator for National Science Foundation projects including AERPAW, a large-scale testbed he co-designed, and Open Artificial Intelligence Cellular, which explores AI-empowered control and testing systems for 6G wireless research. He is an expert in open-source software for software radios. He pioneered the open-source implementation of the 4G long-term evolution wireless protocol, enabling researchers to leverage commercial off-the-shelf hardware for software-defined radio experimentation.

Extremely Wideband RF Spectrum Operations

Abstract: The MITRE Extremely Wideband RF Spectrum Operations (EWO) project is increasing electromagnetic spectrum agility and dominance through analog and digital convergence. Developed under MITRE’s internal R&D program and in collaboration with government and industry, EWO is developing and integrating next-generation wideband technologies, including modular phased array antennas, RF electronics, and Direct RF FPGA System-in-Package (SiP) / System-on-Chip (SoC) devices, establishing a government-owned reference implementation system for creating advanced multi-function wideband capabilities. A major part of this effort includes leveraging digital convergence to enable real-time wideband dynamic spectrum access. Specifically, using industry standard 100GbE interconnect to route high-throughput IQ samples within a network of heterogeneous host processing devices and software-defined radios (SDRs). Our solution follows best practices to achieve high-bandwidth data offload from SDR to Host for receive applications and incorporates a new innovative MITRE technique to achieve scalable and efficient high-bandwidth digital RF transmit from Host to SDR for transmit applications. Together, these capabilities enable game-changing full-duplex high-bandwidth communication between Host and SDR, enabling the next generation of distributed wideband adaptive communications, radar, and electronic warfare applications.

Presenter: Ken Schmitt is a lead embedded systems engineer for The MITRE Corporation in Bedford, MA and leads an internal R&D effort targeting next-generation FPGA SiP/SoC SDR capabilities. He specializes in full system level design and development, bridging the gap between application space, hardware, and software to map high-performance real-time signal processing applications to next-generation heterogeneous compute architectures. Ken received his B.S. in Computer & Systems Engineering and Computer Science from Rensselaer Polytechnic Institute and M.S. in Electrical and Computer Engineering from Georgia Institute of Technology.

RF Fingerprinting Testbed and Classification Experiments

Abstract: Radio Frequency Fingerprinting (RFFP) classification is a method for identifying transmitting radios based on the signal that propagates over the air. It has been proposed as a low-energy, computationally efficient alternative for authenticating wireless transmitters for IoT devices and as a spoof-resistant alternative to MAC layer authentication methods. The RFFP literature has shown machine learning (ML) as a viable RFFP technique, but there are still unresolved questions to warrant RFFP as a viable real-world authentication technique. The testbed design is pivotal in identifying bias caused by day-to-day variations and creating generalizable datasets that span various dynamic channel environments and a larger set of transmitters. Several sources of bias may stem from SNR miscalculation, uncharacterized cable/connector losses, hardware selection, and ambient temperature factors. Creating datasets that generalize to real-world transmitters and operate in dynamic channel environments is challenging because of the scale of the problem. The number of transmitters that can be tested in a wireless testbed is less than the number of wireless devices in the real world. Regardless of the testbed used, the researcher should be aware of sources of bias, the limitations of the testbed to measure those biases, and the limitations of the dataset generality. This presentation will discuss techniques for mitigating sources of bias in the testbed, compare mitigation techniques, and show how they can be applied to improve ML models. This research was generously supported by MIT Lincoln Laboratory and Air Force Office of Scientific Research (AFOSR) Defense University Research Instrumentation Program (DURIP) via the grant entitled “Enhancing 5G Security Via Analysis of RF Hardware Characteristics and Spectral Behavior”.

Presenter: Adriyel V. Nieves is currently finishing his Ph.D. from Worcester Polytechnic Institute. He received an Electrical Engineering B.S. and M.S. degree from Pennsylvania State University in 2015 and 2020, respectively. His research interests include 5G communication systems, machine learning, and system-level design in communication systems.

Synthesis Imaging with Vector Sensor Arrays

Abstract: Radio astronomy observations at frequencies below 10 MHz could provide valuable science, such as measuring the cosmic dark age signal in the redshifted 21-cm hydrogen absorption line, detecting exoplanetary auroral emissions which lead to inferences about magnetic fields and atmospheres, and characterizing the effects of solar wind and coronal mass ejections on the magnetospheres of solar system planets. Despite their value, few measurements in the sub-10 MHz band have been made. At frequencies below 10 MHz, the Earth’s ionosphere reflects, attenuates, and distorts radio waves, making radio astronomy in this band only possible from space. However, a spaceborne array would need thousands of electrically-small antennas to reach the sensitivity required for detecting faint astronomical signals, and it would need to be positioned far from the Earth to reduce the impact of Earth-based radio interference. Using more efficient antennas would minimize the number needed, and using antennas that are robust to interference would reduce the required distance from Earth. To this end, we consider constructing the array out of vector sensor antennas. These advanced antennas consist of three orthogonal dipoles and three orthogonal loops with a common phase center, and their benefits include direction-finding and polarimetric capabilities, but they have not been considered for this application previously. We show that vector sensors can be twice as sensitive, 6-10 dB more robust to noise, and provide four times more Fisher information during interferometry than tripoles, simpler antennas that are commonly considered for space applications.

Presenter: Kat Kononov received B.S. and M.Eng. degrees in Electrical Engineering in 2012 and 2013 from the Massachusetts Institute of Technology (MIT). She is currently a Ph.D. candidate in the Department of Aeronautics and Astronautics at MIT and an associate technical staff member at Lincoln Laboratory. Her research is on space systems and computational imaging with vector sensor arrays. Prior to starting the Ph.D. program, Kononov worked on wireless communication and radar technology at Lincoln Laboratory.

Adaptive and Robust Tracking and Acquisition on a software-defined open-source GNSS receiver

Abstract: With how powerful and integral global navigation satellite systems (GNSS) have become within nearly every aspect of our society and daily lives, a layperson may assume that we must take for granted the technology behind these everyday tools. As with many radio technologies, however, passionate individuals have continued to push back against the idea that this technology is beyond the reach of the individual, promoting through word and action that GNSS is the domain of everyone. In this presentation, we will discuss how students in our lab at Northeastern University are using the open-source GNSS-SDR project to develop, test, and prototype next-generation advancements in GNSS technologies, and the role that SDR plays in making that possible. We will highlight two projects, focusing on the development of the acquisition and tracking stages to handle real-time changes in variable background radio interference and deliberate spoofing conditions using dynamic, Bayesian covariance estimation and robust statistics, respectively. These developments aim to produce a receiver which can independently adjust to adverse and changing conditions without the need for direct human intervention. We will discuss the algorithms and design considerations behind these improvements and the challenges and advantages to their implementation within the GNSS-SDR framework.

Presenter: A Ph.D. candidate in Electrical Engineering at Northeastern University, Gerald LaMountain focuses his research efforts on the fields of dynamic estimation, classical statistics, communications, and positioning, navigation, and timing (PNT) technologies including GNSS and other sensing systems. His research contributions span the academic, industrial, and open-source domains: from his work on multiple sensor projects at Raytheon BBN Technologies, to his involvement in the Google Summer of Code (GSoC) program as both a developer and mentor for the GNSS-SDR project. These experiences have provided a broad skill set and insights into modern radio technologies and algorithms, positioning him as a committed researcher and contributor to the development of sensor systems and estimation technologies.

Space Weather Monitoring with Novel Radar Systems: The 2024 Eclipse

Abstract: The upper atmosphere and ionosphere are becoming increasingly more relevant to our day to day activities thanks to an expanding commercial space industry and our increasing reliance on critical infrastructure in space such as communication satellites and position, navigation and timing systems. These systems have to contend with the near Earth space environment, specifically the ionosphere and our own upper atmosphere, which are severely undersampled and are active areas of scientific interest. MIT Haystack has been working with a number of different sensor modalities to better understand the upper atmosphere and ionosphere. Recently, two HF radar systems have been developed to study these regions of our near earth space environment: The Zephyr Meteor Wind Radar System and the Electro-Magnetic Vector Sensor Ionospheric Sounder (EMVSIS). The Zephyr system measures the wind patterns of the upper atmosphere (between 80 km – 105 km height) by using radar scattering from meteors as a tracer for the wind. EMVSIS is an evolution of ionospheric sounding radar systems with new types of waveform coding and antenna design to measure the bottom side ionosphere. With these two systems working together researchers will be able to better understand how the neutral upper-atmosphere and ionosphere interact together to get a more holistic understanding of the system. The great American 2024 eclipse was used as a deployment goal for these two systems. The results of this deployment and ongoing plans will be discussed, along with the utility of SDR in the development and design of these systems.

Presenters: John Swoboda is a Geospace Research Scientist at Haystack Observatory. He holds B.S. and M.S. degrees from Rensselaer Polytechnic Institute along with a PhD from Boston University, all in electrical engineering. His research interests include radar signal processing and their application to space weather monitoring. He is currently the primary investigator for the EMVSIS project.

Ryan Volz is a Research Scientist at MIT Haystack Observatory with interests in signal processing, statistical estimation, and novel instrumentation applied particularly to radio science. He earned a BS degree in Aerospace Engineering from the Pennsylvania State University in 2007, an M.Phil degree in Engineering (Control Systems) from the University of Cambridge in 2008, and MS and PhD degrees in Aeronautics and Astronautics from Stanford University in 2009 and 2015, respectively. He and colleagues at CU Boulder are currently developing the Zephyr meteor radar network, a novel MIMO system designed to estimate the 3-D wind field in the upper atmosphere by way of meteor trail scattering.

Tutorial Information

Hands-On Satellite Communications Workshop

Abstract: In this hands-on workshop, MathWorks product experts will walk you through a series of online exercises. These guided exercises will give you the opportunity to write and run your own code using Satellite Communications Toolbox and learn how, with minimal coding, you can use the toolbox to streamline your satellite-related workflows.

Highlights:

Brief overview of Satellite Communications Toolbox

Hands-on exercises using MATLAB Online where you will:
–> Set up and launch a satellite scenario viewer
–> Compute and visualize the visibility access between a satellite and a ground station
–> Compute and visualize communications link closure between a satellite and a ground station

Presenter: Mike McLernon is an advocate for communications and software-defined radio products at MathWorks. Since joining MathWorks in 2001, he has overseen the development of numerous PHY layer capabilities in Communications Toolbox, and of connectivity to multiple SDR hardware platforms. He has worked in the communications field for over 30 years, in both the satellite and wireless industries. Mike received his BSEE from the University of Virginia and his MEEE from Rensselaer Polytechnic Institute.

How to Build an FR3 SDR

Abstract: Building an SDR is a boatload of fun. It requires you to get your hands dirty with many tasks, spread across different areas. For example, you will need to build simple circuits using bread-boards, play with evaluation kits, design PCBs, perform HFSS simulations of antennas, program FPGAs, write device drivers, and so on. In this tutorial, we will explore these aspects in greater detail. You will learn the basics of how to design, manufacture, and test your own SDR.

Presenter: Aditya Dhananjay received the Ph.D. degree from the Courant Institute of Mathematical Sciences, New York University (NYU), New York, NY, USA.,He was involved in mesh radio routing and resource allocation protocols, data communication over cellular voice channels, low-cost wireless rural connectivity, OFDM equalization, and phase noise mitigation in mm-wave networks. He currently holds a post-doctoral position with NYU Wireless and is the co-founder of Pi-Radio. He has developed and supervised much of the mm-wave experimental work at the center. He has authored several refereed articles (including at SIGCOMM and MobiCom). He holds one patent and two provisional patents in the millimeter-wave space.

mmW-OAI: An FR2-enabled OAI Testbed

Abstract: Enter mmW-OAI, an FR2-enabled OAI testbed developed by TMYTEK in collaboration with Allbesmart. Already deployed in Japan, this solution blends millimeter-wave technology with OpenAirInterface (OAI) to furnish a comprehensive testing environment spanning from user equipment (UE) to the core network. In this tutorial, we delve into the intricacies of mmW-OAI, equipped with 5G beamformers simulating gNB and UE array antennas, a frequency converter, and a robust PC housing the latest OAI stack. Participants will gain hands-on experience with controlling TMYTEK FR2 devices—including a 24-44 GHz up/down converter (UD Box) and a 28 GHz mmWave beamformer (BBox)—using SDR development environments. We’ll explore API integration, control calls, DLL imports, and more. Moreover, mmW-OAI caters to diverse UE scenarios, accommodating three distinct UE types: OAI UE, Commercial UEs, and COTS UEs. OAI UE provides a customizable platform ideal for research and development purposes, while Commercial UEs offer compatibility with established standards for real-world testing. COTS UEs, on the other hand, enable rapid prototyping and deployment, facilitating swift experimentation and validation of 5G concepts. With mmW-OAI, researchers can explore various applications, such as evaluating beamforming techniques and antenna configurations in mmWave environments, assessing 5G protocols’ performance under real-world conditions, investigating URLLC and mMTC use cases, and prototyping innovative applications like AR, VR, and autonomous vehicles in 5G networks.

Presenter: Toabis Huang, an accomplished professional with a strong background in electrical and control engineering, pursued his master’s studies at National Chiao Tung University from 2008 to 2010. During this time, he specialized in Electrical and Control Engineering. Prior to his master’s, Toabis completed his undergraduate studies at the same institution, majoring in the same field from 2004 to 2008. Toabis holds the position of Software Manager at TMYTEK in New Taipei City. In this role, he oversees the mmW OAI offering and leads the development of OAI solutions from architectural design to implementation. Before joining TMYTEK, Toabis gained valuable experience as a Senior Engineer at Scarlettech in Taipei and also contributed as a Senior Engineer at HTC. Toabis Huang’s expertise lies at the intersection of software development, engineering, and cutting-edge technologies.

FPGA Programming on the USRP with the RFNoC Framework

Abstract: This workshop provides a tutorial on the RFNoC framework, including a discussion on its design and capabilities, demonstrations of several practical examples, and a walk-through of implementing a user-defined RFNoC Block and integrating it into both UHD and GNU Radio. The RFNoC (RF Network-on-Chip) framework is the FPGA architecture used in USRP devices, specifically the E310, E312, E320, X300, X310, N300, N310, N320, N321, X410. The RFNoC framework enables users to program the USRP FPGA, and facilitates the integration of custom FPGA-based algorithms into the signal processing chain of the USRP radio. Users can create modular, FPGA-accelerated SDR applications by chaining multiple RFNoC Blocks together and integrating them into both C++ and Python programs using the UHD API, and into GNU Radio flowgraphs. Attendees should gain a practical understanding of how to use the RFNoC framework to implement custom FPGA processing on the USRP radio platform.

Presenter: Neel Pandeya is a Principal SDR Engineer and Group Manager at National Instruments in Austin, Texas, USA. His background and interests are in open-source software development, kernel and embedded software development, wireless communications, 4G/LTE and 5G/NR networks, DSP and signal processing, FPGA programming, and software-defined radio (SDR). He has previous technical management experience and university teaching experience, and formerly held a TS/SCI government security clearance. He is a co-founder and co-organizer of the New England Workshop for SDR (NEWSDR), and is a co-organizer of the GNU Radio Conference (GRCon) as well as the 5G Workshop at IEEE MILCOM. He holds a Bachelor’s Degree in Electrical Engineering (BSEE) from Worcester Polytechnic Institute (WPI), and a Master’s Degree in Electrical Engineering (MSEE) from Northeastern University (NEU), and is a member of IEEE and Eta Kappa Nu (HKN). He has an Amateur Radio License, and is aspiring to obtain a private pilot license.

Community Spotlight Talks

Poster 1: Innovation in SDR-Centric Wireless Engineering Education

Authors: Galahad M. Wernsing, Alexander M. Wyglinski
Affiliation: Worcester Polytechnic Institute
Abstract: Software defined radio (SDR) technology has become an integrative part of wireless communications and networking educational experience of undergraduate students with respect to hands-on project-based learning of the latest techniques and approaches for over-the-air connectivity. With SDR costs having dramatically decreased over this time period in addition to a substantial increase in functionality, new approaches can be employed in the classroom to provide students with new insights on wireless connectivity, spectrum, and propagation. In this poster, we provide the latest approaches and insights on how SDR can be used to introduce students to a commercial standard (Bluetooth Low Energy) in an over-the-air controlled environment to understand the operations of the Physical and Medium Access Control layers across several real-world scenarios.

Poster 2: A Guide to Build an RF Fingerprinting Testbed

Authors: Adriyel V. Nieves, Alexander M. Wyglinski
Affiliation: Worcester Polytechnic Institute
Abstract: For RF Fingerprinting applications, the testbed design is pivotal in identifying bias caused by day-to-day variations and creating generalizable datasets that span various dynamic channel environments and a larger set of transmitters. Several sources of bias may stem from SNR miscalculation, uncharacterized cable/connector losses, hardware selection, and ambient temperature factors. Creating datasets that generalize to real-world transmitters and operate in dynamic channel environments is challenging because of the scale of the problem. The number of transmitters that can be tested in a wireless testbed is orders of magnitude less than the number of wireless devices in the real world. Regardless of the testbed used, the researcher should be aware of sources of bias, the limitations of the testbed to measure those biases, and the limitations of the dataset generality. This work shows some techniques for characterizing the testbed.

Poster 3: Enhancing Astronomical Discoveries: Real-Time Data Processing at the Allen Telescope Array

Authors: Luigi Cruz
Affiliation: SETI Institute
Abstract: This poster presents the next-generation data processing pipeline of the Allen Telescope Array based on the NVIDIA Holoscan SDK. The upgrade significantly improves operational efficiency by delivering data to scientists faster and enabling the simultaneous execution of diverse observation algorithms, including traditional and machine learning-based approaches. All this is possible by applying techniques such as RDMA to offload data processing tasks to the GPU resulting in a reduced need for additional processing hardware. This translates to lower power consumption and a more cost-effective system while maintaining a telescope-independent interface.

Poster 4: Private 5G Standalone Networks using Shared Spectrum

Authors: Bob Stewart, Sam Yoffe, Louise Crockett, Malcolm Brew
Affiliation: Neutral Wireless Ltd
Abstract: We will share our experience of developing SDR technology for private 5G networks for broadcast and live event applications featuring SDR radio designs, and collaborations with technology and media partners. Notably, we have demonstrated the optimisation of 5G-SA private networks for broadcast video, achieving low latency operation and biasing the network to give greater capacity in the uplink (supporting the transfer of high data-rate video to the production hub). Neutral Wireless (a spin-out company of the Univ of Strathclyde StrathSDR team), along with partners at the BBC, designed and deployed the world’s largest popup private 5G SA network for the live event HD video uplink streams to broadcast at the Coronation of King in London, May 2023. With the existence of a private network using bands of 100MHz of n77 spectrum in the UK, it’s not about network slicing, it’s all about making use of available (shared!) spectrum. The poster will look also ahead to Summer 2024, where we are designing and providing the 5G SA radio network, working alongside a number of top tier technology companies to provision private 5G SA networks for broadcast and media use cases for one of the world’s largest sporting events (taking place somewhere in Europe!).

Poster 5: RFSoC with PYNQ: Research, Development, and Learning

Authors: Louise Crockett, Bob Stewart
Affiliation: University of Strathclyde
Abstract: Developing SDRs with embedded System on Chip (SoC) devices is attractive due to their computational capabilities and reprogrammable nature, but can also be complex. The poster focuses on the AMD Zynq UltraScale+ Radio Frequency SoC (‘RFSoC’) platform, which integrates DACs and ADCs with Programmable Logic and a Processing System. This single-chip solution is very capable, but has a significant learning curve! Our research leverages the PYNQ software/hardware framework to target RFSoC devices. PYNQ is an open-source project from AMD that makes it easier to use SoC devices. So far, we have used the RFSoC-PYNQ combination for SDR prototyping, spectrum analysis and instrumentation, deep learning for wireless, and there is more to come! This poster will share some examples. The StrathSDR group has developed a free ~650-page book to support SDR engineers working with the Zynq UltraScale+ RFSoC. This book is for research students and professional engineers, and it includes an extensive set of supporting practical examples. The project is a collaboration between StrathSDR and AMD. It enabled the practical know-how developed by PhD researchers working in the lab to be captured and disseminated. We highlight this resource as potentially being of interest and use for the SDR community.

Poster 6: gr-pdw: An OOT Module for Pulse Descriptor Word (PDW) Generation

Authors: James Humphries
Affiliation: GTRI
Abstract: Pulse descriptor words (PDW) are measured properties of detected RF pulses. PDWs are often utilized for radar sensor characterization, identification, and emulation. Pulse measurements are typically provided as an option on high-SWaP, high-cost laboratory test equipment or as custom FPGA firmware which is not easily scalable to multiple SDR/RF platforms. gr-pdw is an out-of-tree (OOT) module for GNU Radio developed by GTRI that performs pulse detection and PDW generation. The intention is that gr-pdw provides the ability for any commercial-off-the-shelf (COTS) SDR to perform PDW measurements. Currently it is capable of measuring pulse width, power, frequency, and time-of-arrival (ToA) along with noise power. gr-pdw also provides blocks for writing PDWs to a log file and controlling the flowgraph parameters remotely over a network connection. Testing has been performed with a USRP B210 in both laboratory and field settings with measurements comparable to currently used PDW generators. Blocks have been prototyped in Python with plans to port them to C++ for improved performance in high pulse-rate scenarios. GTRI plans to open source this OOT after initial capabilities have been fully tested and implemented. This paper presents gr-pdw theory of operation, descriptions of block functions, and test results.

Poster 7: Hypernetwork for Adaptive Self-Interference Cancellation with Continual Learning in Full-Duplex Wireless Systems

Authors: Sheikh Habibul Islam, Xin Ma, Chunxiao Chigan
Affiliation: University of Massachusetts Lowell
Abstract: Full-duplex (FD) wireless systems offer the potential to double spectral efficiency by facilitating simultaneous transmission and reception on the same frequency. However, effective implementation of FD systems necessitates robust self-interference (SI) cancellation to manage the interference from simultaneous transmission. Due to the dynamic nature of wireless environments, it is crucial for adaptive SI cancellation (SIC) to learn and adjust in real-time to maintain reliable FD communication. In this work, we present a novel continual learning-based hyperNet adaptive SIC solution designed for dynamic, time-varying wireless channels. Our solution achieves SI cancellation near the noise floor even under dynamic conditions, adapting swiftly to new channel characteristics and significantly reducing SI. We validated our approach through simulations of a full-duplex transceiver system that closely mirrors real-world conditions. This includes Orthogonal Frequency-Division Multiplexing (OFDM) with all radio frequency (RF) impairments, addressing both linear and non-linear SI, and simulating dynamic wireless channels typical of pedestrian, vehicular, and urban environments.

Poster 8: Real-Time Wideband Spectrum Awareness and Signal Characterization

Authors: Jin Feng Lin, Erika Caushi, Charles Montes, Eric Savage, Ruolin Zhou
Affiliation: University of Massachusetts Dartmouth
Abstract: This research introduces an innovative spectrum awareness tool that merges spectrum sensing and signal characterization, leveraging a highly optimized 1-dimensional Faster Region-Proposal Convolutional Neural Network (FR-CNN). In cluttered radio frequency environments with simultaneous transmissions, our FR-CNN model, tailored for 1D signal processing, integrates machine learning for Angle of Arrival (AoA) estimation, demonstrating superior efficiency and accuracy over conventional methods. Through over-the-air (OTA) testing with software-defined radios (SDR), our framework extends to signal characterization, exhibiting adaptability to wideband signals for effective analysis across diverse frequencies and waveforms. Additionally, our study evaluates machine learning methods for AoA estimation in wireless communication systems, demonstrating robustness and stability in synthetic and OTA test scenarios. The real-time visualization of sensing results offers critical insights, including the signal’s AoA, center frequency, bandwidth, and modulation type, thereby enhancing spectrum monitoring and management capabilities significantly.

Poster 9: Preamble-Defined Network Slicing

Authors: Matthew Silverman, Nicholas Wycoff, Spencer Albano, Shengli Zhou
Affiliation: University of Connecticut
Abstract: We implemented preamble-defined physical-layer network slicing with Software Defined Radio (SDR). This was our entry for the 2023-24 AFRL SDR University Challenge and won first place. Specific devices slices of the network can be targeted by selecting a specific preamble. Devices with an assigned preamble different than that of the transmitted message will not attempt to decode it. Network slicing typically occurs in layer 3 or higher of the OSI model, so in contrast, we demonstrate network slicing on the physical layer. This was accomplished by appending preambles with good correlation characteristics to the beginning of Wi-Fi and Zigbee packets. These preamble signals must have spiky autocorrelation with low sidelobes for detectability, and low cross-correlation so that each preamble is distinct and nearly orthogonal. To demonstrate this concept, we created a multi-standard network using both Wi-Fi (802.11) and Zigbee (802.15.4). This consisted of an access point that can communicate across Wi-Fi and Zigbee devices, three emulated Wi-Fi devices and two Zigbee devices using SDR. There are five preambles to define network slices, three for Wi-Fi, and two for Zigbee. The proposed physical layer network slicing scheme allows for efficient and flexible operation of next generation communication networks.

Poster 10: Class-Incremental Learning for Baseband Modulation Classification: A Comparison

Authors: Charles Montes, Todd Morehouse, Ruolin Zhou
Affiliation: University of Massachusetts Dartmouth
Abstract: This paper presents a comprehensive study on the capabilities of class-incremental learning in the context of baseband modulation classification. Despite the growing interest in incremental learning, there is a lack of information specifically addressing its application in the radio frequency (RF) domain for modulation classification. This study aims to fill this gap by investigating the effects of incremental learning when applied to different increments of classes, methods, and types of methods like exemplars. We explore various methods including non-incremental learning, cross-entropy distillation, and bias correction, and evaluate their performance in the context of incremental learning. Multiple incremental scenarios are considered including adjusting the step size of the number of classes learned, and adjusting the number of exemplars used during incremental training. The capabilities of incremental learning are gauged based on their ability to continually learn new classes without forgetting the previously learned ones. The evaluation is performed on the DeepSig 2018A dataset, which comprises 24 classes, providing a robust platform to assess the capabilities of incremental learning. The results of this study provide valuable insights into the potential of incremental learning in baseband modulation classification.

Poster 11: Efficient Neural Networks on the Edge with FPGAs by Optimizing an Adaptive Activation Function

Authors: Yiyue Jiang, Andrius Vaicaitis, John Dooley, Miriam Leeser
Affiliation: Northeastern University
Abstract: Neural networks have been applied to Digital Predistortion (DPD) in the last decades due to their promising capability for nonlinear modeling. The implementation of neural networks (NN) on edge devices enables local processing of wireless data but faces challenges such as high computational complexity and memory requirements when deep neural networks (DNN) are used. Shallow neural networks customized for specific problems are more efficient, requiring fewer resources, and resulting in a lower latency solution. An additional benefit is that it is suitable for real-time processing on edge devices. Shallow neural networks may have decreased accuracy compared to DNNs. We demonstrate that a customized adaptive activation function (AAF) can meet the accuracy of a DNN. We designed an efficient FPGA implementation for a customized segmented spline curve neural network (SSCNN) structure to replace the traditional fixed activation function with an AAF. Our proposed SSCNN implementation uses 40% fewer hardware resources compared to the DNN with similar accuracy. We validate this computationally efficient and memory-saving FPGA implementation for digital predistortion of RF power amplifiers using the AMD/Xilinx RFSoC ZCU111 while using less than 3% of the available resources, leaving space for additional real-time processing while achieving clock speed of 221 MHz.

Poster 12: Tiny4FSK – Modern, Lightweight High-Altitude Tracking Systems

Authors: Maxwell Kendall
Affiliation: New England Sci-Tech
Abstract: Tiny4FSK is a tracking system using FSK (Frequency-Shift Keying) to encode digital tracking data. It is built for long-distance high-altitude tracking, where high speed protocols are required. It makes use of the Horus Binary v2 protocol, in conjunction with the 4FSK modulation to provide a robust tracker. Tiny4FSK is intended to be used for high altitude balloons, and will be tested on several over the next year. It is based on an embedded 4-layer PCB, using a ARM-based microcontroller. It is decoded with an SDR connected to a computer, using the HDSDR program to receive the signals. Then, using a virtual-audio cable, it can be paired with the Horus-GUI Windows application to decode the 4FSK and Horus Binary v2 to post the position data to an online global database called SondeHub Amateur. This was built as an alternative to a reprogrammed radiosonde, which weighs more and is bigger than Tiny4FSK.

Poster 14: EDGES – searching for the signal from the first stars

Authors: Rigel Cappallo, A.E.E. Rogers, Judd Bowman, Colin Lonsdale, John Barrett, Nivedita Mahesh, Steven Murray
Affiliation: MIT Haystack Observatory
Abstract: There is a theoretical global signal that should be detectable across the entire sky that is directly linked to the formation of the first stellar objects, some 13 billion years ago. This is known as the 21-cm cosmological signal. The EDGES antenna has been specifically designed and engineered to detect this ~ 0.2 K signal, which is hidden within a ~ 5000 K background in the 50-100 MHz band. This precision measurement has required exquisite engineering and RFI mitigation strategies, including deployments in isolated areas of the globe. This poster will explore the engineering strategies employed by the EDGES team, as well as previous and current results.

Poster 15: Impact of suplemental coverage from space on radio astronomy

Authors: Samuel The, Frank Lind, Daniel Sheen
Affiliation: MIT Haystack Observatory
Abstract: The proliferation of satellites in low-Earth orbit, forming mega-constellations, enables connectivity even in the most remote places. Direct-to-cellphone coverage service at 1.9925 GHz is even currently being tested by Starlink satellites. However, these constellations, composed of hundreds or even thousands of satellites, can pose significant challenges to radio astronomy. Indeed, radio telescopes are very sensitive instruments used to observe the extremely faint objects that are of interest to radio astronomers. Each satellite can emit signals (intentionally or unintentionally) that are considered as radio frequency interference for astronomical data and can even damage the instrument. Although transit of satellites through the main beam of radio telescopes could be avoided by coordinating astronomical observations and satellite coverage, the congregation of sidelobes-to-sidelobes interactions between the telescope’s antenna and the many satellites is also a growing concern. This work investigates the potential impact of the supplemental coverage from space on radio astronomical data, accounting for sidelobes interactions. The 18.3m Westford radio telescope of the MIT Haystack Observatory is used in this study to design a data model that will be compared to real data in an upcoming observation campaign.

Sponsors/Exhibitors

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