IEEE North Jersey Section

[] Are you interested in using Software-Defined Radio (SDR) to create an amateur radio system? This presentation will describe efforts to integrate USB SDR modules with a Raspberry Pi 4 running the Raspberry Pi OS and open-source radio applications such as Software-Defined Receiver (GQRX) and weak signal communication software (WSJT-X) to create a modular portable amateur radio system. Topics include: - Radio and RF apps, including a GNU Radio FM receiver flowgraph - Quite Universal Circuit Simulator (Qucs) with microstrip RF filter Layout simulation - Octave OpenEMS electromagnetic field solver - KiCad layout example - Raspberry Pi Pico microcontroller programming examples Speaker(s): Jay Morreale Agenda: 7:00 PM Networking and Announcements 7:10 PM Presentation Virtual: https://events.vtools.ieee.org/m/480384

Dear Members of the IEEE North Jersey Section, The IEEE North Jersey Section is pleased to announce its annual "Awards Banquet Event" to be held on Sunday, May 4, 2025 at the Birchwood Manor, in Whippany, New Jersey, from 3 pm until 6 pm. The Section pays tributes to the new Fellows in our Section, as well as the recipients of major IEEE and other technical awards, IEEE Region 1 Awards, Section Awards and Society Awards. We look forward to seeing at this event to celebrate the award recipients Please use the vToos link to make reservation. Please register all attendees by completing the name, address, and e-mail entries on the form. Spouses and guests are welcome. (Please register each guest separately) For more information please contact: Ken Oexle, Awards Committee, Email: k.oexle@verizon.net Russell Pepe, Awards Committee, Email: russell.pepe@atm1.com Adriaan Wijngaarden, Awards Committee, Email: (mailto:adriaan.de_lind_van_wijngaarden@nokia-bell-labs.com) Ajay Poddar, Awards Committee, Email: akpoddar@ieee.org Emad Farag, IEEE North Jersey Section Chair, Email: enfarag@ieee.org Agenda: 2:30pm-3:00pm Photo Session for Award Recipients 3:00pm-4:20 Cocktail Hour, Welcome and Networking 4:30pm-5:00pm Award Ceremony 5:00pm-6:00pm Coffee/Desserts Tickets/Fees are applicable as follows: EXCOM members plus one guest attend free Award Recipients plus one guest attend for free Invited IEEE dignitaries plus one guest attend for free Advance registration is required for all attendees: $15 for IEEE student members (Discounted Rate) $35 for non-EXCOM members and additional guests $50 for non-IEEE members The capacity of the location is limited, so please make your reservations early. Birchwood Manor, 111 N Jefferson Rd, Whippany, New Jersey, United States, 07981

Deep neural networks make it possible to learn key characteristics of data without having to assume mathematically tractable models. This in turn results in an ability to compress data in a model-free way. One of the promising areas for the application of deep learning to the physical layer of communication networks is compression. Hundred-fold compression with a small loss of the CSI in massive MIMO systems has been shown to be both feasible and necessary. However, model-free and data driven compression comes with a downside: the encoding and decoding models need to be trained on a large set of CSI arrays indicative of a wide spectrum of propagation and environmental conditions. As a result, in the early stages of the deployment of deep CSI compression models, it would be necessary to detect if and when users’ channels have drifted significantly away from the distribution of the CSI data on which the deep compression model was trained. In this paper, we present both 1) a technique for detecting harmful channel drift and 2) a lightweight scheme for fine-tuning the deep compression models to adjust to such shifts. Using public-domain synthetic channel data as well as 3GPP-compliant simulated data, we demonstrate the practicality of our proposed deep compression and detection framework. We close with recommendations for a viable implementation of the proposed drift detection by the standards bodies. Co-sponsored by: New Jersey Coast Section Chapters, ComSoc Chapter, COM19, Jt Chp,ED15/MTT17/PHO36 and Jt. Chapter,SP01/CAS04, and North Jersey Section Chapter,COM 19 Speaker(s): Dr. Kursat Metsav, Agenda: 06:30 p.m. - Introduction of Dr. Kursat Metsav 06:35 p.m. - Presentation by Dr. Kursat Metsav 07:10 p.m. - Question & Answer session Virtual: https://events.vtools.ieee.org/m/476641

This webinar will provide a comprehensive examination of the role of Digital Pre-Distortion (DPD) in mitigating distortion effects, enhancing linearity, and improving overall system efficiency. Participants will acquire insights into advanced DPD techniques, practical implementation strategies, and the latest tools for effective analysis of Error Vector Magnitude (EVM) and DPD performance. A thorough understanding of EVM is essential for assessing the quality of transmitted signals. The discussion will include an in-depth analysis of amplifier testing and its critical importance in evaluating system performance. Through the presentation of real-world examples and case studies, this session aims to equip engineers and industry professionals with the knowledge necessary to optimize their designs. Co-sponsored by: IEEE North Jersey Section Speaker(s): Martin Lim Virtual: https://events.vtools.ieee.org/m/481323

Robotics and AI Trip at Montclair Enjoy the robotics and AI project demonstrations and hands-on interactions with robots and AI systems at Montclair. [] Bldg: CCIS, 1 Normal Ave, Montclair, New Jersey, United States, 07043

Talk 1 The half-wave dipole is a widely used antenna in Amateur Radio and other communications. It is often one of the first antennas studied in college courses. Professor R.W.P. King dedicated over 100 years to studying dipoles, and his accurate measurements continue to validate modeling software. Professor John Kraus, through his 1950 book Antennas, inspired many in the field, including the speaker. This presentation will explore key topics related to the half-wave dipole. First, we will assess the accuracy of various antenna modeling codes, using a unique surface model in FEKO as a reference dipole compared to wire Method of Moments (MoM) methods. We will also review the famous formula 468/f, which calculates the length of a half-wave dipole in feet (where f is in MHz), and discuss its effectiveness and common misconceptions. It does not reliably tune all antennas to resonance for different wire or tubing diameters, so we will provide a simple interpolation method for adjustments. Lastly, we will present a new design method for constructing a half-wave dipole antenna that is independent of the conductor's diameter, whether wire or tubing. Talk 2 Nearly every aspect of society relies on Positioning, Navigation, and Timing (PNT) services from Global Navigation Satellite Systems (GNSS) like the Global Positioning System (GPS). However, GPS signals are vulnerable to spoofing and jamming due to their unauthenticated nature and weak signal strength at the Earth's surface. Implementing such attacks is relatively easy with low-cost hardware and open-source software, leaving many regions susceptible to these threats. Research over the past few decades has focused on improving PNT performance amid jamming and spoofing, typically categorized into five main approaches: 1) signal processing methods, 2) antenna-based methods, 3) artificial intelligence (AI) techniques, 4) non-GNSS sensors, and 5) hybrid methods combining various strategies. This presentation will provide an overview of GPS and GNSS technologies, common attack strategies, and various mitigation methods, primarily focusing on antenna-based techniques. It will introduce a taxonomy of these techniques aimed at enhancing signal reception by maximizing authentic GPS signals and minimizing those from attackers. The presentation will highlight well-known techniques and ongoing research and discuss key research gaps and future directions. Co-sponsored by: IEEE North Jersey Section AP/MTT17, ED/CAS, and PHOTONICS Chapter Speaker(s): Prof. James K. Breakall, Jack L. Burbank Agenda: 4:150 PM - Refreshments and Networking 4:30 PM-6:30 PM: Talk by Prof. James K. Breakall, Penn State University, University Park, PA 16802 and You do not have to be an IEEE Member to attend. Refreshments are free for all attendees. Please invite your friends and colleagues to take advantage of these Invited Lectures. Room: 202, Bldg: ECEC, 141 Warren St, New Jersey Institute of Technology, The Lewis and Julia P. Kieman Conference Room, Newark, New Jersey, United States, 07102