The media often likes to portray new technologies as the result of a flash of brilliance in the night, or the work of some solitary genius. In fact, if you look at the development of the telephone, the light bulb or the first airplane, each of these inventions was based on the convergence of basic concepts that were well known in the scientific community. The inventors built upon prior knowledge to create something that was practical and versatile. RFID has gone from a solution to problem (1969), a “breadbox” test system (1970), the birth of an industry and in the future a nano device (150 nm or less). This paper will present how RFID went from a concept to an industry and possibly to an invisible device. This technology will truly enable fulfillment of the promise of the Internet of Things (IoT). The recent developments of producing a true nano RFID which will lead to a nano distributive meshed computer system. These devices can be styled “Intelligent Surfaces” (IS). These nano RFIDs (NRs) may prove to be a truly disruptive technology. With the addition of artificial intelligence (AI) the NRs could become a significant total system.
NOTE: This Special Session includes also the following presentation:
16:00 – 16:20 (ORSS 2024 Best Student Paper) Concept of Radiation Capsule With Electromagnetic Actuation To Enable High Dose Rate Brachytherapy for Iodine-125 – Authors: Junia Nguyen; Luke Ezzell; Cassidy Moreau; David Roque; Peter Hesketh; David Yu; Hoseon Lee, Kennesaw State University, USA.
We propose a novel design for RFID tags – ID-Yarn, in which an RFID tag is integrated into a yarn suitable for weaving, embroidery, or seam attachment to fabric. ID-Yarn comprises an RFID transponder chip soldered with a conductive filament onto the chip pads. The chip and the filament are then enveloped with non-conductive fibers, creating a yarn structure. The conductive filament within the ID-Yarn serves as a dipole antenna, and various dipole antenna configurations can be achieved by shaping the ID-Yarn into different geometries. We have introduced three dipole variations: a dipole with varied arms for conjugate-matching the chip impedance, a dipole with meander-lined arms, and a dipole with looped arms. Simulations and prototypes of these variations demonstrate the feasibility of ID-Yarns. Notably, the ID-Yarn shaped into a looped dipole geometry exhibits the best performance.
We present a method for resolving multiple chipless RFID tags in a read zone using phase measurements conducted during a raster scan with a directive reader antenna. We differentiate between 3 chipless RFID tags with up to 2 shared resonance frequencies in the 3 – 4.4 GHz band, that are spaced as close as 6.4 cm apart. Furthermore, we automate the process of tag identification and location estimation with a positional error of less than 8 mm. We also present a relationship between tag resonant frequency and minimum tag spacing. Future directions are also discussed.
Relay attacks are a powerful tool for defeating challenge-response authentication protocols. Current solutions for detecting these relay attacks utilize round-trip time distance-bounding. Unfortunately, secure implementations of distance-bounding require dedicated ultra-wideband hardware that only provide low data rates, operate at relatively short distances, and require dedicated hardware. In this paper we propose a novel symmetric-key protocol that simultaneously provides challenge-response authentication and relay attack detection in the near field and far field, through the utilization of a random IIR filter as a challenge. The protocol utilizes the channel estimation in an OFDM communication system to perform the evaluations. To evaluate the performance of the protocol, hardware experimentation on software-defined radios to observe the false-positivity and false-negativity rates of relay detection under normal communications and a relay attack.
Using Ultra High Frequency (UHF) Radio Frequency Identification (RFID) for full transparency and traceability in a pharmaceutical supply chain can be a challenging goal to accomplish. The susceptibility of RFID to dielectric materials poses significant challenges in implementing a successful RF-enabled system. Within the pharmaceutical industry, those dielectric materials can be the constituents of a drug, physical state of the drug or even the packaging. This study builds off a previous publication by the authors highlighting the attenuations that happen across different drug formulations. This paper presents an experimental design using three commercially available UHF RFID tags, which their manufacturers claim are designed for small products in the healthcare and pharmaceutical sectors. The tags were tested on two control samples and four liquid suspension over-the-counter drug formulations. This study aimed to investigate the correlation between the pH and conductivity of these products and the performance of RFID tags, including tag sensitivity and theoretical read range, with the ultimate objective of enhancing RFID efficiency in asset management systems. Although there were no correlations between RFID performance, conductivity, or pH, there was a significant difference in the performance of the tags attached to the ibuprofen liquid suspension when it contained dye in comparison to the ibuprofen sample that did not.
This study introduces a customizable passive radio frequency identification (RFID) toolkit supporting bodily movements as well as hiding, showing, or touching objects as gaming inputs (controlling activities). The established toolkit is functional without onboard power sources, making its implementation into clothing, walls, floors, and any self-made game controllers simple and cost-effective. We developed gaming scenarios connecting the physical world to gaming. To play a game, players in the clothing-based scenario can move different parts of their body, such as their arms and legs, whereas players in the floor- and wall-based scenarios can move their bodies right or left in the gaming space. On the other hand, object-based scenarios allow any object to be turned into a game controller. In practical testing, the percentages for average correct input detection, non-detection, and false input were 77%, 14%, and 9%, respectively, which is promising. However, there were a few challenges in detectability and reliability, which must be solved for the next prototype iteration.
In this paper, we introduce the structure of a pressure stripline sensor with a flexible hollow top layer. Applying force or pressure to the structure causes a linear variation in the height of the top layer with respect to pressure. This change in height results in the effective dielectric coefficient of the flexible hollow layer varying with pressure, leading to alterations in the phase constant (β) and the phase of S21 under pressure. The performance of the sensor was evaluated based on the measurement of the phase to calculate the pressure.
Wireless power transfer has the potential to distribute energy to diverse applications, such as electric vehicles while they are operating, extending their range. This paper presents an antenna designed and simulated to receive RF power in a drone. To enhance aerodynamic performance, features such as holes and wedges were introduced to allow for improved airflow. In this preliminary study, the antenna maintains well-performing characteristics, achieving a gain of 17.7 dBi for a 16-element patch array. The modifications contribute to a lighter design, prompting additional studies to explore further enhancements in performance and efficiency.
This work concerns the operation of a battery-less transponder operated by intentionally generated wireless signals in the 2.4 GHz ISM band. The wireless signals consist of a power supplying data stream and special Bluetooth messages. In response, the transponder back-scatters these messages to a conventional Bluetooth receiver. Our implementation uses two regular mobile telephones, one for transmitting the wireless signals, the other for receiving the scattered signals. The back-scattering applies frequency shifting of the incident Bluetooth messages for separating transmission and receiving processes. The special Bluetooth messages include specifically designed bit sequences that by themselves serve as short Bluetooth messages that are appropriately coded for detection by the Bluetooth receiver. In effect, generation of response messages is delegated from the battery-less transponder to the transmitting telephone. Experiments show that 2 MHz frequency shifting achieves better performance and/or efficiency than 4 or 6 MHz shifting, the latter based on third harmonics. At 2 MHz, the active power consumption of the transponder is uW and the wireless operational range reaches 6 cm, which is a 50% improvement over our previous work. Thus, the proposed design improves basic communication between a battery-less transponder and mobile telephones, which encourages further endeavors in this direction.
This paper presents an harmonic sensor based on a RECCO reflector which can be used to modulated the backscattered wave at the 2nd harmonic as a function of its rotational speed. This property allows one to monitor the rotational speed remotely in real-time. Additionally, the transponder can also be identified based on the variation of its response as a function of the frequency. Finally, this transponder presents an improved robustness compared to classical motion-modulated transponders and can be used in complex dynamic environments.
8:20 – 8:40
Title: In-Band Ambient FSK Backscatter Communications Leveraging LTE Cell-Specific Reference Signals
Authors: Jingyi Liao, Aalto University, Finland; Xiyu Wang, Aalborg University, Denmark; Kalle Ruttik, Aalto University, Finland; Riku Jäntti, Aalto University, Finland; Dinh-Thuy Phan-Huy, Orange, France.
A long term evolution (LTE) signal is ubiquitously present, which make it an attractive signal source for ambient backscatter communications (AmBC). In this paper, we propose a system that uses LTE cell-specific reference signals (CRSs) transmitted by a base station as an ambient source and channel estimator at the user equipment (UE) as an AmBC receiver. One of the challenges in AmBC is direct path interference (DPI): The direct signal from the transmitter to the receiver is several orders of magnitude stronger than the scattered path. We propose a solution that operates withing the original LTE band. In order to mitigate the DPI, the backscatter device (BD) performs a frequency shift keying (FSK) modulation that introduces an artificial Doppler shift to the channel which is larger than the natural Doppler but still small enough such that it can be tracked by the channel estimator at the UE. We demonstrate the feasibility of the proposed system by Proof-of-Concept implementation and compare its performance against the simulation results. Measurement results show that we could achieve bit error probabilities less than (10^{-2}) with ambient LTE signal having SNR of 5 dB operating on 486 MHz band having 7.68 MHz bandwidth.
8:40 – 9:00
Title: Circular Slot-based Microstrip Circularly Polarized Antenna for 2.45 GHz RFID Reader Applications
Authors: Kamlesh Patel University of Delhi South Campus, India; Amit Birwal, University of Delhi, India; Sanjeev Singh, University of Delhi, India.
Abstract: The paper presents a new design for a mobile 2.45-GHz passive Radio Frequency Identification (RFID) reader, featuring a compact, broadband, and circularly polarized antenna. The antenna proposed consists of two stacked square patches separated by an air gap for a wide-band impedance bandwidth. The antenna is printed on a double-sided 1.6 mm FR4 substrate with an overall dimension of 65×65×11.27 mm3. By introducing and optimizing a pair of symmetrical ring slots in both the square patches, a good Axial-Ratio Bandwidth (ARBW) and symmetrical broadside radiation patterns are achieved. The reader antenna shows a measured S11 bandwidth (S11<-10 dB) from (2.3-2.7 GHz) and ARBW (< 3 dB) from (2.39-2.48 GHz). The peak gain of the proposed antenna is 6.2 dBi and is obtained at the center frequency of 2.45 GHz. Measurements of the proposed antenna are discussed to obtain the read range and field of view, which confirms its suitability for RFID Reader Applications and other Internet of Things (IoT) based applications.
9:00 – 9:20
Title: A Sub-Threshold Microwave RFID Tag Chip, Compatible With RFID MIMO Reader Technology
Author: Sanaz Haddadian, Circuit and System Technology, Heinz Nixdorf Institute, University of Paderborn & Member of Institut Für Photonische Quantensysteme (PhoQS) Paderborn University, Germany.
Abstract: We present a fully integrated radio frequency identifications transponder chip operating at 5.8 GHz, which is compatible with the class-1 generation-2 of the Electronic Product Code protocol (EPC-C1 G2). The tag chip including the analog front-end and the digital baseband processor, are designed in the sub-threshold regime (0.5 V) with a total supply current of less than 50 μA. As a power scavenging unit, a single-stage differential-drive rectifier structure is designed and fabricated with standard threshold voltage (SVT) MOS elements in a commercial65-nm CMOS process, to provide 0.8 V of rectified voltage. Measurements performed on the fabricated single-stage structure show a maximum power conversion efficiency of 69.6% for a 22 k load and a sensitivity of -12.5 dBm, which corresponds to more than 1 m of reading range. The power conversion efficiency at this range is about 64%.
For the localization of autonomous vehicles, the use of passive chipless RFID technology is of significant interest, as it would enable self-localization strategies complementing RADAR, LIDAR or GPS based approaches and thus lead to much needed situation dependent redundancy. Here, additively manufactured ceramic materials and components are discussed for this purpose. In general, ceramics are considered low loss with regard to electromagnetic properties and highly resilient in corrosive, or high temperature environments, potentially making them an excellent choice for long lasting chipless RFID technology. However, the processing of ceramic components, especially with mu-m resolution is challenging and generally regarded inflexible as it is associated with the use of molds. The use of additive manufacturing for this purpose brings the digital design freedom of 3D-Printing to ceramic processing, which puts a focus on achievable structure sizes as well structural quality of the printed material for signal processing applications. Therefore, this contribution focuses on the electromagnetic properties of additively manufactured Alumina (Al2O3) and Zirconia (ZrO2) discussing the tuneabilty of parameters such as permittivity, loss tangent and the occurrence of birefringence in dependence of processing and the resulting material quality. The technology is then used to demonstrate a retroreflective tag solution for the W-Band, consisting of a flattened Luneburg lens structure in combination with a 3D-2bit Tag for which a readout of +/- 80° is achieved, making it useful for self-localization purposes. It will be demonstrated that the tag can endure temperatures above 1000°C, while enabling code readout. In this context the device is usable for temperature sensing purposes, as the permittivity of the devices changes by 67ppm/K, resulting in a quantifiable frequency shift. Further, an outlook will be given on how this sensor fusion concept can be extended, to enable retroreflective tags with biosensing capabilities.
This paper proposes a novel misalignment-resilient resonator for high-efficiency wireless power transfer, harvesting, and sensing in wearable applications. The selected topology is derived from the strongly coupled magnetic resonance principle, demonstrating robust power transmission and resilience to misalignment. Our system demonstrates resilience to angular misalignment for the first time using an array of SCMR resonators while maintaining reasonable efficiency over long distances. The proposed system operates at 40 MHz and has been designed and simulated on a gauze fabric substrate. The results show that for rotational misalignment ranging from 10 to 90 degrees, the system maintains an efficiency of 80% across the entire range. Additionally, with a distance of 20 cm between the transmitter and receiver, the system exhibits 80% efficiency. The efficiency was also tested for misalignment along all three axes, revealing that an 80% efficiency level is achieved even when the misalignment on the x, y, and z axes simultaneously reaches 10 cm. This system can be integrated with a power harvesting circuit to collect DC power for body-worn sensors.
This paper presents a fully integrated and compact rectenna system designed for radio frequency energy harvesting at 2.45 GHz, aimed at powering low-power applications such as semi-passive and active radio frequency identification systems. The rectenna system co-optimizes the antenna and rectifier, eliminating the need for an impedance matching network, thereby reducing transfer losses and its size. A reconfigurable central power management system and a supercapacitor are incorporated, featuring maximum power point tracking, enabling efficient power harvesting and delivery. The antenna design is based on a meandered-line planar inverted-F antenna, which provides compactness, ease of integration on a low-cost FR4 substrate, and an omnidirectional radiation pattern. Over-the-air power conversion efficiency measurements were conducted, demonstrating high efficiency at low input power levels. The system’s functionality was further validated by powering a wireless body temperature sensor application, featuring a packet update rate of 14m24s for an input power level of -10 dBm.
Modern Implantable Medical Devices (IMDs) provide wireless connectivity for remote monitoring and device programming. However, this connectivity also exposes IMDs to potential cybersecurity and physical threats, which can compromise patient safety. In this paper, we propose a novel miniaturized unit cell of an epidermal Radio-Frequency IDentification (RFID)-based wireless programmable Frequency Selective Surface (FSS) designed to protect IMDs from unauthorized electromagnetic interference (EMI) and ensure secure communications. The proposed shield minimizes power requirements and achieves a highly compact form factor by employing Single-Pole-Single-Through (SPST) switches in place of conventional PIN diodes. Numerical simulations and experimental evaluations confirm the efficacy of the shield in attenuating signals in the Medical Implant Communication Service (MICS) band, with a shielding effectiveness of more than 25 dB. This solution represents a novel approach to enhancing the resilience of IMDs against physical and cyber threats.
The emergence of contactless and battery-free powering for bio-electronics, such as wearable devices and implants, has sparked significant interest in wireless power transfer (WPT) and energy harvesting technologies. This paper presents the first active metasurface array for microwave Wireless Power Transfer (WPT) systems, allowing near-field programming of the electromagnetic fields. We introduce a conformal vertically-stacked multi-layer power transmitter composed of beamformer Integrated Circuits (ICs). Thanks to per-element phase/amplitude control, the metasurface array breaks the dependency between Electric and Magnetic fields dictated by the geometry of the transmitter in single-element power transmitters. To increase the maximum deliverable power to miniaturized bio-electronics under the Specific Absorption Rate (SAR) safety limit, we leverage the near-field programming to suppress SAR distribution while adjusting the intensity of the Magnetic (Electric) field at the receiver’s location. We evaluate the performance of this approach through electromagnetic-circuit co-design and simulation and define a new Figure of Merit (FoM) to quantify the maximum deliverable power.
This paper investigates how the number of antenna elements in retrodirective arrays of transponders affects the robustness of backscatter systems like radio-frequency identification (RFID) systems against fading. A channel model describing the behavior of retrodirective transponders is developed, and simulations are conducted to analyze the fading characteristics based on different array sizes. The results show that increasing the number of antenna elements significantly reduces fading initially, but further increases in the number of antennas beyond a certain point provide diminishing returns. This study provides insights into the design and optimization of retrodirective transponders to improve the reliability of backscatter communication systems.
This paper presents a frequency selective backscatter modulator for the 2.4 GHz industrial, scientific, and medical (ISM) band. Unlike conventional wideband backscatter modulators, which modulate every incoming signal that is incident on an antenna, a frequency selective modulator mitigates undesirable spectral pollution by preferentially backscattering signals over a desired range of frequencies and minimizing backscatter elsewhere. The modulator architecture presented here is designed for Wi-Fi (IEEE 802.11) and Bluetooth backscatter devices operating in the 2400-2483 MHz ISM band. Three different band-selection filters are presented, based on microstrip and low-temperature co-fired ceramic (LTCC) implementations. Additionally, three different modulators based on varactor diodes, PIN diodes, and pHEMT FETs are presented. The wideband differential reflection coefficient (|∆Γ|) is simulated and measured for each combination, demonstrating the frequency selective backscatter properties of the presented modulator architecture. For example, the pHEMT based frequency selective modulator exhibits a 5856 MHz 3 dB modulation bandwidth (∆Γ_3dB) without filtering, while the addition of an LTCC filter reduces ∆Γ_3dB to only 328 MHz. This modulator has an energy-per-bit figure of merit of only 1.9 pJ/bit.
This study presents a novel intra-body identification (IBID) technology that uses capacitive backscatter for data transmission. The primary goal of IBID is to facilitate transmission of arbitrary data (e.g., IDs) between a battery-powered interrogator and a batteryless tag through physical interactions. Unlike traditional RFID, which relies on electromagnetic fields in the air for backscattering, IBID uniquely utilizes the finite conductivity of human skin and air-coupled capacitance to enable backscatter communication. In this study, we explore a configuration where the interrogator is worn on the body, and the tags are affixed to everyday objects for human activity monitoring. Specifically, we investigate capacitive backscatter performance when acquiring IDs from two object models: a cylindrical handle and a rectangular switch panel. Preliminary results demonstrate the successful implementation of intra-body capacitive backscatter and the system’s ability to interrogate binary IDs. However, variations in the tag electrode dimensions result in fluctuating path gain, even over short distances, causing distortion in demodulated bits. To address this, we designed and implemented a proof-of-concept tag circuit on a PCB that transmits bursts of 16-bit binary values within one capacitor charge cycle and an interrogator that reliably demodulates and decodes an 8-bit binary ID.
Ambient Backscatter Communication (AmBC) represents a recent breakthrough in wireless communication technology. It enables devices to communicate wirelessly using ambient radio frequency (RF) signals rather than generating their own carriers. This advancement holds considerable promise for Internet of Things (IoT) applications, particularly in addressing the challenge of power efficiency. In this paper, we introduce, for the first time in literature, a novel prototype of a backscatter modulator tag that works in the ambient 5G-NR signal (3.5 GHz). An experimental functional validation of the 5G-NR backscatter tag is presented by using BPSK modulation. Additionally, we have explored the prototype feasibility focusing mainly on the differentiation of power levels between the direct link and the backscattered signal, highlighting a critical challenge in 5G-NR backscatter communication.
Radio-frequency identification (RFID) technology is widely used across industries due to its affordability, low power requirements, and compact form factor. Its adaptability has led to expanded research into applications beyond traditional tracking. This study investigates the use of commercial RFID antennas to determine package orientation by analyzing Phase and RSSI readings. Using machine learning models, we evaluated sixteen unique configurations and package orientations. Results show that the optimal placement of an RFID tag can achieve up to 92.3% accuracy in orientation estimation, with the most effective setup utilizing a single antenna and tag. This research presents an innovative approach to posture detection, underscoring RFID’s potential for advanced tracking and monitoring applications.
One of the emerging technologies in Industry 4.0 is Radio Frequency Identification (RFID), due to its low cost, non-line-of-sight communication and low energy consumption. RFID can be used in a variety of applications, such as injecting RFID tags during the manufacturing process of plastic products, in the medical field to improve the logistics of medical equipment or in manufacturing and supply chain management. Studies have been carried out to solve some problems in these applications, such as determining the direction of RFID tags, but these use a set of antennas. To solve this problem, it was implemented machine learning (ML) algorithms to determine the direction of the objects using one single antenna. Of the three classifiers, Random Forest, Extra Trees, and Bagging Classifier, Extra Trees and Random Forest were the best classifiers with an accuracy of over 86.65% and 84.96% respectively for determining the direction of movement. Under optimal conditions, the Tag 2, reached an accuracy of 94.42% when 25 samples were acquired. This study analyzed the influence of tag positioning and reading on determining movement direction using a single antenna. This proposal can enable industries to monitor logistics processes more effectively, particularly in controlling the transition of materials between sections with reduced costs.
In this work, we combine time-of-flight (ToF) and angle of arrival (AoA) measurements to determine the position of an radio-frequency identification (RFID) transponder. This enables precise tracking of the use and location of tools, for example. A frequency-modulated continuous wave (FMCW) radar at 24 GHz is used to determine the ToF. The modulated backscatter from the transponder allows for clutter suppression. Two receiving antennas are employed in the radar for AoA determination. The investigation shows that the localization of a transponder is possible in a realistic environment. The range is limited to a few meters due to the low signal-to-noise ratio in this implementation. It becomes evident that tracking tagged objects is feasible with the presented approach using a commercial automotive radar as reader.
This contribution presents a direct positioning algorithm for the movement reconstruction of objects tagged with passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tags in postprocessing. We propose a signal model with the assumption of the movement trajectory being separable in piecewise linear parts with constant velocity in the x-y plane. The reconstruction algorithm consists of a Sequential Importance Resampling (SIR) particle filter using a switched antenna system of 14 antennas in a laboratory room. The estimator reaches the Cramér-Rao lower bound (CRLB) under optimal conditions and provides a Root Mean Squared Error (RMSE) of less than 0.3 m for real-world measurement data.
RFID-based localization refers to determining the position of an object equipped with an RFID tag by analyzing the signals transmitted between the tag and RFID readers. In this paper, we present an exploration of multi-frequency and multi-view localization using UHF-RFID passive tags. We propose an approach exploiting Particle Filter (PF) and Beamforming (BF) imaging methods to enhance the accuracy and precision of RFID-based localization systems. During the offline phase, a controlled dataset was created by collecting backscattered signals from a passive RFID tag at multiple positions and angles using a two-antenna setup at two different frequencies. The collected dataset was analysed using PF and BF techniques to estimate the tag’s location. Preliminary experimental results demonstrate that both methods offer valuable insights into the localization process, with BF providing real-time capabilities and reduced computational complexity, while PF contributes greater accuracy in noisy environments. These findings lay the groundwork for future development of more sophisticated multi-view localization systems.
13:20 – 13:40
Invited Speaker: Matt Reynolds – University of Washington, US
Title: RFID Past, Present, and Future: An academic research perspective
Abstract: Every year, tens of billions of RFID tags are produced, and serve as the edge-devices of the Internet of Things (IoT). These tiny, battery-free, wireless computing devices consume only microwatts of power and cost only a few cents each, fulfilling the seemingly insurmountable goals established by the MIT Auto-ID Center nearly 25 years ago. This spectacular success is only the beginning of the RFID story. In this talk, I will present some of the historical milestones that led to the development of RFID as it is today, and give some future-looking perspective from an academic and industry point-of-view on emerging research challenges that will drive the field forward over the coming years. I will also share some lessons I’ve learned on how some of the most exciting technologies can find success (or failure!) in the commercial marketplace.
13:40 – 14:00
Invited Speaker: Manos Tentzeris (A. A. Jamal) – Georgia Tech, US
Title: From Backscatter to Digital Twins: The Evolving Landscape of Additively Manufactured and Lens-Based RFIDs for Ultra-Long Range, sub-cm Accuracy, and Origami-Inspired Reconfigurability
Abstract: This contribution reviews key advancements in RFID technology over the past decade and proposes future directions for its evolution. Notable progress has been made in additively manufactured and millimeter-wave (mm-wave) RFIDs, enhancing flexibility, scalability, and data throughput. Building on these innovations, we propose developments aimed at enabling ultra-long-range sensing, sub-centimeter localization, and high data rate transfer. We explore trends like origami-inspired reconfigurability, lens-based designs, and machine learning to improve RFID precision and adaptability. Additionally, we discuss the potential for fully energy-autonomous RFIDs and mm-wave technology for high-speed, long-range communication, positioning RFID as a central technology for next-generation IoT applications such as industrial IoT, virtual reality, smart cities, and autonomous vehicles.
14:00 – 14:20
Invited Speaker: Nicolas Barbot – University of Grenoble Alpes, FR
Contributors: Smail Tedjini, Etienne Perret, Nicolas Barbot – University of Grenoble Alpes, FR
Title: Contributions of the LCIS to RFID and future directions for the next decade
The LCIS laboratory was one of the first French laboratories to focus its activity on the RFID technology in the early 2000s. At that time, the UHF technology brought many hopes to solve logistic and traceability problems encountered in the Industry. The background of the LCIS researchers based on RF and antenna design was used to start the first projects on RFID technology. In 2001, the first PhD student working on RFID started his thesis on the design of RFID tags integrated directly into the packaged product. Since then, RFID has remained at the heart of the lab. During the following years, significant efforts have been done to characterize the performance of different UHF tags. The LCIS lab was selected to participate in the writing of the ISO/IEC 18047 standard to define the procedure to characterize and compare the performance of UHF tags. In 2009, the first activity on chipless RFID began at the lab. This promising direction allows one to significantly reduce the price of a tag by removing the silicon chip. Different concepts, which are still in use today, have been developed at the lab such are the use of scatterers to increase the coding density, cross-polarization to improve the robustness of the reading or compliance with the UWB standard. In 2011, new projects started on the UHF technology to transform the current state of the art in RFID-based systems and improve the technology adoption, particularly in retail and healthcare sectors. Different key concepts were developed during that time such as the communication at the third harmonic using conventional RFID chips. In total, for more than 20 years, the LCIS has collaborated with many research labs and companies to address challenging problems using the RFID technology. During the same period, more than 40 PhD students and post-docs have been trained to advanced RFID topics. Today, the LCIS lab is still working actively on the RFID technology and backscatter communications. The new trends that are investigated by the lab includes the exploitation of non-linear effects in the UHF technology, new applications of the chipless technology and time-variant or non-linear transponders. • Non-linear effects in UHF RFID: these effects are present in any UHF RFID tags and are not exploited by commercial readers. According to the signal generated by the reader, harmonics of the incident frequency can be generated which can carry information during the tag reading. This allows one to improve the robustness of the radio link or to bring new functionalities. Intermodulation products can also be generated by UHF chips to detect a tag at a distance higher than its read range. • New applications of the chipless technology, by considering the technology as a whole, including both the tag and the reader. To differentiate itself from barcodes, this technology must tomorrow offer more functionalities while maintaining certain reading flexibility inherent to using electromagnetic waves to interrogate the tag. Through the ERC ScattererID project, the objective is to develop a concept of wireless RF characterization, halfway between the use of resonant cavity principles and a quasi-optical free-space approach. The idea is based on developing a reflectometry technique using resonant backscattering elements. From an application perspective, in addition to having an identifier, the chipless tag should be rewritable, include a sensor function, or allow a user to physically interact with an electronic system. • Time-variant or non-linear transponders represent two new directions to realize the function of identification and sensing using radio frequency signals. These techniques are able to break the time invariance and/or the linearity of the transponders used in the RFID chipless technology. The first direction addresses transponders which can break the time-invariance property by modulating their backscattered field. These transponders actually gather the transponders developed by Stockman and Theremin in the 1940s. The second direction focuses on non-linear transponders which can break the linearity property. These transponders can generate harmonics or intermodulation products which can be easily separated from the signal generated by the reader. Linear time-variant and non-linear transponders and their associated reading systems offer interesting properties to realize both identification and sensing. Finally these transponders are characterized by a read range and a coding capacity which can outperform by a factor 30 the ones associated with any linear time- invariant system.
14:20 – 14:40
Invited Speaker: Riccardo Colella – National Research Council, IT
Contributors: Alberto Arciello, Massimo Merenda – Università Mediterranea di Reggio Calabria, IT Giuseppe Grassi – Univeristy of Salento, IT Riccardo Colella – National Research Council, IT
Title: Towards Memristor-Based Neuromorfic RFID Circuits and Architectures
Abstract: Current RFID chip architectures, optimized for low-power communication and data storage, are inadequate for the computational demands of future IoT applications. While effective for basic identification tasks, these systems fall short in supporting advanced data processing and on-chip artificial intelligence. This paper emphasizes the transformative potential of neuromorphic circuits in RFID technology, enabled by the integration of memristor-based architectures, particularly Resistive Random Access Memory (ReRAM) and crossbar arrays. ReRAM provides significant advantages, including reduced energy consumption and enhanced memory performance, which are crucial for facilitating neuromorphic computing. By leveraging the unique properties of ReRAM and crossbar configurations, RFID systems can evolve into intelligent nodes capable of local processing and real-time decision-making. In the near future, novel neuromorphic RFID circuits could learn from the environment and mimic the behavior of biological neurons, enabling tasks such as pattern recognition and low-power anomaly detection directly within the memory array, by overcoming the current Von Neumann architecture. This could redefine RFID tags, paving the way for more intelligent, efficient, and autonomous systems.
14:40 – 15:00
Invited Speaker: Gaetano Marrocco – University of Roma Tor Vergata, IT
Title: Multiscale RFID Evolution: From Nanoscale Materials to Large-Scale Adaptive Systems
Abstract: This talk will explore emerging research directions that challenge RFID technology across multiple scales, from the nanoscale to the largescale. The multiscale approach underscores how innovations at vastly different dimensions can converge to redefine system capabilities and applications. At the nanoscale, material engineering and precise fabrication techniques unlock novel functionalities, while at the largescale, system-level integration and collective behaviors pave the way for new paradigms in sensing, communication, and security. At the nanoscale, groundbreaking techniques like Laser-Induced Graphene (LIG) enable the fabrication of antennas and sensors on carbon-based substrates without the need for traditional metal conductors. By fine-tuning laser parameters, it is possible to create heterogeneous structures with tailored electrical properties. This approach offers significant advantages, including enhanced device performance, cost-efficiency, and alignment with circular economy principles, promoting sustainability and recyclability. These nanoscale advancements open the door to transformative applications. For example, in smart packaging, RFID sensors can be seamlessly integrated into the packaging material to monitor product conditions such as temperature and humidity in real time, ensuring food freshness and safety throughout the supply chain. Similarly, in the field of implantable prostheses, LIG technology enables the embedding of electronic tattoos on prosthetic surfaces, transforming them into data-generating devices. These systems can track physiological parameters or structural integrity, providing critical insights for personalized healthcare and device management. Furthermore, the performance of LIG-based device can be even improved by electroplating, using the LIG as a mask. Another application field concerns the realization of LIG-based Physical Unclonable Functions for the anti-counterfeiting and integrity assessment of devices. At the largescale, the focus shifts to RFID grids-networks of RFID elements that exhibit emergent behaviors through electromagnetic coupling, a concept introduced a decade ago, that recently matured into viable implementations. These grids, which can be embedded with sensors, exploit near-field interactions to function as unified systems with enhanced capabilities. The electromagnetic coupling amplifies energy scavenging, improves data communication, and enables advanced sensing functionalities. Applications of largescale RFID grids include multifunctional reconfigurable surfaces capable of generating detailed thermal maps, such as those used in microwave hyperthermia treatments. These surfaces can dynamically adjust their interaction with electromagnetic fields, switching wirelessly between transparent and reflective states. A particularly promising application lies in the development of intelligent skins that selectively shield critical devices from electromagnetic cyber-attacks, enhancing the security of cyber-physical systems. Furthermore, the synergy between nanoscale manufacturing and RFID grid configurations offers exciting possibilities for the future of RFID technology. By harnessing nanoscale innovations for large-scale applications, eco-compatible smart skins can be developed that incorporate both sustainability and high functionality. Advances in materials like Laser-Induced Graphene (LIG) enable the creation of extremely thin and flexible structures, ideal for large-scale, lightweight smart skins that can conform to complex surfaces while minimizing environmental impact. In applications such as sustainable building and the protection of critical devices, these smart skins could serve as intelligent, adaptive barriers that respond dynamically to environmental conditions, shield sensitive equipment, and contribute to data collection. Moreover, the potential for creating scalable, reusable, and recyclable structures signals a shift towards a more circular and sustainable approach to RFID applications. In summary, the multiscale approach – combining innovations from the nanoscale to large-scale implementations – opens the door to transformative applications that go beyond traditional boundaries, marking a new era for RFID technology in sustainable and multifunctional systems.
The real-time adaptive nulling of a digital beam-former is crucial for receiving weak signals in a high RFI or RF denied environment. The Howells-Applebaum and MVDR adaptive beamformers use the Weiner optimum solution to ensure that RFI sources are blanked out in an array processor. In this paper, we create a custom 32-channel fully-digital array operating at 5.7-5.8 GHz, with real-time FPGA processing for both adaptation and subsequent beamforming with RFI suppression. Real-time measurements with up to three RFI sources show correct real-time digital beamforming in the FPGA processor. The developed microwave and digital systems along with hardware accelerated Howells-Applebaum array-null adaptation architecture will be used as a building block to create RF identification, location, spectrum sensing, and wireless communications that are resilient to jammers and RFI sources in the environment.
In dense RFID systems, efficient coordination between multiple readers is crucial to prevent reader-to-reader interference (RRI) and ensure optimal system performance. As the number of readers and tags increases, static frequency and time-slot assignments become insufficient to handle dynamic network conditions, leading to collisions, missed tag reads, and degraded throughput. In this paper, we propose a decentralized neighborhood discovery and management technique for RFID systems operating in high-density environments. Our approach minimizes interference and improves tag read accuracy by dynamically adjusting communication parameters like frequency and time slots based on current system conditions, which are updated by periodic information exchanges between readers.
True time delay beamforming is required when the bandwidth of interest is a major fraction of the center frequency. A true-time delay multi-beam beamformer for an N-element array produces N simultaneous beams using O(N^2) delay units. In this work, we reduce the delay complexity down to just O(N). An implementation path for a wideband 8-beam multi-beam beamformer with direct-RF chiplets from Intel Altera Agilex-9 is described.
As the recent advances in mmWave/5G technologies become increasingly available, the potential for wireless Internet of Things (IoT) devices for precise localization, and high data- rate communication systems become highly feasible for AR/VR applications. At the same time, it is essential that the new generation of mmWave systems for IoT applications are low- cost, energy-efficient, easily-scalable, reliable and compact. This work presents some of the recent efforts in mmWave/5G RFID systems that combine novel designs for overcoming the challenges in long-range interrogation, wide-angular coverage, and power consumption. This work describes the state of the evolving field of mmIDs through paradigm examples in literature that enhance mmID localization and orientation, making mmID-based AR/VR applications more feasible.
15:20 – 15:40
Invited Speaker: Nuno Borges Carvalho – Universidade de Aveiro, Portugal & Instituto de Telecomunicacoes, Portugal
Title: Use of SWIPT – Simultaneous Wireless Information and Power Transmission as a way to leverage RFID technologies to berryless sensors.
Abstract: The use of Simultaneous Wireless Information and Power Transmission (SWIPT) is emerging as a transformative approach to advancing RFID technology for batteryless sensors. This presentation will explore how SWIPT can be leveraged to expand the potential of RFID in creating self-sustaining sensors capable of operating without the need for traditional power sources. By enabling the concurrent transmission of data and power, SWIPT allows for more robust and versatile applications, especially in scenarios where maintaining a battery-free, energy-efficient setup is critical. Key topics to be discussed include backscatter approaches for high-bit-rate sensors and their applicability in long-range applications. Specifically, the presentation will cover Frequency-Shift Keying (FSK) backscatter methods and approaches utilizing harmonic tags, both of which offer innovative pathways for improving data throughput and range in batteryless sensors. Additionally, we will examine strategies for decoupling DC sensor functions from RF sensors, allowing for greater adaptability in sensor design and integration across diverse RF-powered environments.
15:40 – 16:00
Invited Speaker: Rahul Bhattacharyya – Auto Lab – MIT, US
Title: Beyond ID: Positioning RFID for sustainable IoT applications using AI, smart materials and augmented optics. RFID technology is well positioned for low-cost, mass identification of assets in pretty much every industry segment. This makes it a prime candidate for pervasive sensor data generation, enabling data driven analytics in many applications where information is currently lacking or insufficient. This talk showcases examples in cold chain, health and safety, circular economy, healthcare and others where RFID has the potential to add significant value over the state of the art. I demonstrate how this is achieved with the help of advancements in other disciplines such as AI, smart materials and computer vision. Future prospects of innovation with RFID using interdisciplinary innovation is also discussed.
16:00 – 16:20
Invited Speaker: Luca Catarinucci – University of Salento, IT
Title: Extending RFID-Inspired Backscatter Modulation Across Existing Technologies
Abstract: RFID technology has evolved significantly over the past 15 years, driven by scientific and industrial research that has enabled large-scale adoption. Today, companies are increasingly investing in RFID, relying on a technology that has reached a high level of refinement. However, despite this progress, several promising research tracks remain open, with the potential to further advance RFID, driving broader adoption and integration across diverse applications. Among these research directions, one appearing particularly relevant aims to address a key limitation of RFID technology: while the cost of RFID tags is extremely low, the reading infrastructure remains complex and resource-intensive, which hinders adoption in applications that require widespread, unobtrusive integration-such as smart home systems or other highly specialized, low-power environments. To overcome this, a promising and underexplored approach involves leveraging RFID through backscatter modulation on top of pre-existing wireless technologies-without modifying their inherent properties or embedding active transmitters on the tags. This approach offers interesting new possibilities for RFID applications, particularly in environments where adopting new infrastructure is impractical or economically unfeasible. By implementing RFID functionality through backscatter modulation that interacts seamlessly with existing systems such as WiFi networks, BLE (Bluetooth Low Energy) platforms, LoRa, microwave motion sensors (MMSs) commonly used in security, and others, this approach could leverage current resources to enable new identificatoin, localization, zero-power sensing and asset-tracking capabilities. For example, in a hospital setting, patient tracking and asset management could be performed by adopting RFID-over-WiFi tags through the existing WiFi network, reducing the need for additional RFID readers and cabling. In industrial or agricultural environments equipped with LoRa networks, RFID-over-LoRa tags could track tools and machinery across large areas, leveraging LoRa coverage for inventory management without new RFID infrastructure. Likewise, in buildings with MMS-based security systems, adding RFID-over-MMS tags to valuable assets would enable precise identification alongside movement detection, reducing false alarms and enhancing asset monitoring through the existing MMS infrastructure. This approach, though intriguing, is still in its early stages and reveals numerous challenges that merge telecommunications expertise with circuit design, antenna engineering, and microwave technology, just to mention some. Indeed, one key issue involves maintaining signal integrity and managing interference to ensure robust communication while utilizing native signals from existing wireless systems. Another area of focus is optimizing backscatter modulation efficiency, ensuring the tag’s reflected signal maintains sufficient strength for reliable data reception, especially in dynamic environments with variable multipath and fading effects, while accounting for limitations in maximum allowed power in certain technologies. Antenna design optimization also plays a crucial role, requiring conformal, dual-purpose antennas that meet backscatter requirements while remaining compatible with the existing system specifications. Lastly, advancing energy harvesting and power management will be essential, as ultra-low-power circuit designs that leverage ambient RF energy to power the tags can ensure functionality without compromising efficiency. All these aspects are explored in a previous paper, where we introduced backscatter modulation over MMS, leveraging the Doppler effect to preserve the native functionality of the specific technology. Key details from that work will be revisited in the presentation of this study. Future research will need to address these and additional challenges, such as ensuring seamless interoperability and minimizing latency. Successfully tackling these issues could enable RFID to become more deeply integrated into everyday systems, broadening its application scope and bridging the gap between traditional RFID limitations and the smart environments of tomorrow.
16:20 – 16:40
Invited Speaker: Gregory Durgin – Georgia Tech, US
Title: Optimal Modulation Improvements for Gen 3 and the Applications that they Would Unlock
Abstract: The Gen2 UHF RFID standard is twenty years old, which means that it contains almost none of the research insights from the last two decades of the IEEE RFID community. Innovations in microwave band usage, energy-harvesting waveforms, modulation, group-proofing, encryption, localization, motion capture, subspace detection, and on and on are effectively “waiting on the shelf” for the next generation protocol. We will demonstrate one such innovation involving optimal modulation coding schemes that get much closer to information theoretic limits than the FM0 and Miller-modulated subcarrier schemes of Gen2. We discuss a number of new RFID applications that would benefit from these changes.
16:240 – 17:00
Invited Speaker: Sara Amendola – Radio6ense, Rome, IT
Title: Application-driven Challenges for RFID-based IoT platforms
Abstract: In the early 2010s, the number of scientific publications of RFID technology reached a plateau, marking a phase of consolidation and technological maturation. This pivotal moment presented an opportunity to transition from academic exploration to industrial impact. In this context, we founded Radio6ense, a spin-off of the Pervasive Electromagnetic Lab of University of Rome Tor Vergata, with the goal of transforming the most mature research outcomes into tangible industrial value. Over the past decade, we have deployed pioneering RFID sensor networks across diverse sectors, including manufacturing, automotive, healthcare, and pharmaceuticals, integrating them into challenging and unusual scenarios, while pushing the boundaries of what the RFID technology can reliably achieve with state of the art HW/SW components. Through this journey, we have uncovered critical application-driven challenges that the RFID community must address to meet industry needs. These challenges range from overcoming bottlenecks in sampling rates for monitoring dynamic phenomena, to mitigating the susceptibility of RFID front-end systems to electromagnetic interference when interfacing with external probes, and addressing cybersecurity vulnerabilities in connected IoT platforms. Grounded in our extensive field experience ‘”on the field”, This talk will spotlight these challenges, with the aim of inspiring new research directions that can bridge innovation and application, ensuring RFID’s continued impact for years to come.
NOTE: This Special Session includes also the following presentation:
9:00 – 9:20 (ORSS 2024 Best Student Paper) Investigating the Impacts of Device Geometry and an Alternative Write Current Scheme on Write Time and Switching Energy of SOT-MRAMs – Authors: Seongjin Kim; William Montello; Avanish Narumanchi; Azad Naeemi; Md Nahid Haque Shazon, Georgia Institute of Technology, USA.
The widespread adoption of RFID technologies has highlighted the urgency of adopting more secure solutions to counter the growing risks of cloning and attacks. Traditional unique identification systems have significant limitations in terms of resistance to attacks, necessitating the adoption of emerging technologies. In this context, non-volatile memories (NVM) technology offers a promising alternative due to their ability to create unique identifiers and secure key based on non- replicable physical imperfections, providing inherent security. This contribution aims to propose a novel control logic that exploits the variability of the resistances of Resistive Random Access Memory (ReRAM) to implement a secure and efficient Physical Unclonable Function (PUF), thereby optimizing the performance of an RFID system.
The need for reliable detection of ASK-modulated RF signals in passive RFID tags, especially under varying power levels and low modulation depths, drives the design of a highly sensitive demodulator. One of the major factors in increasing the sensitivity is the comparator’s ability to detect the small voltage differences. This paper presents the design and implementation of a high sensitivity voltage mode demodulator for passive RFID tags. Compared to the weighted average demodulator, it eliminates the need for a calibration circuit to increase the difference between the input voltages of the comparator. A rail-to-rail input comparator with built-in negative offset is proposed, which enhances the sensitivity by increasing the input voltage difference of the comparator, providing reliable detection across a wide range of power levels and data rates. The design is implemented in commercially available 0.18-µm CMOS technology and operates from a 1.2V supply. The demodulator can demodulate the minimum input power of -9dBm and modulation depth of 10% at a power consumption of 1.04µW.
In typical passive UHF RFID systems, tags rely on backscattering, where they modulate a reflected signal by switching impedance states, powered solely by the reader’s RF signal. In contrast, active RFID tags offer enhanced communication capabilities but require an internal power source. This work introduces a novel hybrid approach that combines electromagnetic energy harvesting and backscattering, utilizing two distinct carrier frequencies. A 2.45 GHz transmitter powers a rectenna and encodes a frequency sweep from 20 kHz to 100 kHz using a simple mixer. After energy harvesting, the device modulates its 5.8 GHz backscattering antenna with the down-converted signal. This results in a backscattered 5.8 GHz signal that is easily distinguishable from the transmitter signal owing to the introduced frequency offset. This method enhances the reliability and modulation options of passive RFID tags. Finally, a fully passive, batteryless remote control application is explored to demonstrate the potential of this approach.
This paper presents a novel solution for space occupancy monitoring, specifically designed for optimizing HVAC system efficiency in modern buildings. The proposed system utilizes battery-less RFID motion sensor tags which is maintenance-free, cost-effective, and compact. The proposed RFID tags integrate an energy harvester, rectifier, PIR motion sensor, and microcontroller, enabling comprehensive coverage, including blind spots, for accurate occupancy data collection. By covering all spaces, including blind spots, the system provides comprehensive occupancy data for energy-efficient HVAC control. Experimental results show that These ultra-low-power tags can detect occupancy within a circle with a 7-meter diameter. Measurement results show that the proposed tag functions correctly up to 2.8 meters away from the reader, with the reader operating at the maximum power level permitted by the RFID protocol’s power mask. Within this range, the energy harvester block consistently generates a stable 3.3V output voltage across the RFID frequency range used in North America (902-928 MHz). Additionally, the energy harvester block was tested separately under various load conditions, and the measurement results are provided. These results demonstrate that the energy harvester can maintain a stable voltage even at the tag’s peak energy consumption.
In this paper, a UHF-RFID reader system is developed for 2D localization of sheep in sheepfold environments. It is built on an innovative compact Electronically Steerable Parasitic Array Radiator (ESPAR) type antenna leveraging superdirectivity and signal processing algorithms that utilize the amplitude and phase of retro-modulated signals from tags for localization. Experimental validation of the RFID system achieved lamb localization with read ranges of five to six meters and positional accuracy of less than 1 meter in most cases.
This paper compares respondents’ preferences for RFID-based Smart Post Boxes concept in the Czech Republic before and after the COVID-19 pandemic. Survey data from 2019 and 2024 show an increase in favorability for contactless parcel delivery, reflecting the shift in consumer behavior. Key findings include financial savings from reduced failed deliveries, societal benefits like lower emissions, and a 10.87% reduction in the payback period. Despite rising competition, the Smart Post Boxes concept remains favored by the respondents for its security and convenience, supporting its potential role in smart city logistics.
The micro-environment inside pharmaceutical packages is critical for drugs integrity and safety. Long-term stability and rate of degradation of solid-packaged products are evaluated by pharmaceutical industries with Accelerated Predictive Stability (APS) studies performed inside climatic chambers. To keep the packages’ micro-environment unaltered, wireless and batteryless sensors are preferable to monitor internal temperature and humidity levels. Passive Ultra High Frequency (UHF) Radio Frequency IDentification (RFID) antenna-sensors, provided with Integrated Circuits (ICs) embedding temperature (T) and relative humidity (rH) sensors, can be made compact up to the size of a pill to be loaded inside the package in contact with the product to be monitored. Thus, provided that a suitable wireless reading system is deployed inside the climatic chamber, a real-time and wireless monitoring of drug status from the inside of the bottle can be performed during the tests. This paper presents an experimental characterization of a four-antenna chamber-embedded RFID reading system able to provide a uniform radio coverage ensuring ≃100% reading of all the in-package T/rH probes over time, optimized in size to fit into a pill-like case.
Life expectancy has significantly increased in recent decades, partly thanks to the growing pervasive use of technology that has produced sophisticated diagnostic equipment and multi-functional medical devices, often interconnected and powered by artificial intelligence-based algorithms. The next transformative step is the dematerialization of many devices, integrating them directly onto the skin or within the human body. This shift holds immense potential for prediction, prevention, and personalized care. Radio frequency Identification, when coupled with unconventional materials and highly embedded into tissues and medical objects, is perhaps the only technology capable to support this digital transformation from the micro to the macro scale. This presentation will introduce RFID-based flexible and stretchable electronic devices that adhere on the body like a second skin capable of digitalizing body parameters, restoring touch functionality, and enhancing traditional senses, thereby laying the groundwork for the Tactile Internet. The second part of the speech will delve into RFID-powered Cyber Prostheses. This involves transforming conventional, passive, and bulky orthopedic and cardiac implanted devices into data-generators by leveraging the hidden antennas within them, or by engraving a graphene circuit on the prothesis itself by laser patterning. These technologies promise a significant leap in self-knowledge, enabling unprecedented identification of our healthy baseline and the early detection of anomalies. The last part of the talk will be devoted to the open issues related to security/privacy and data ownership, the resolution of which will be crucial for the mass adoption of this new framework.
This paper examines the use of the C band (5030-5091 MHz) for command-and-control (C2) communication with unmanned aircraft systems (UAS). A channel plan is suggested and key system settings for C2 communication are tested. MATLAB simulations are used to evaluate system performance in free-space environ- ments. Signal-to-Interference-plus-Noise Ratio (SINR) and Reference Signal Received Power (RSRP) are measured at different UAS heights. Antenna arrays from single antenna up to 10×10 arrays are analyzed to measure the Front-to-Back Ratio (FBR) and simplify the system. The study uses a 20 MHz bandwidth and considers a system load of 50 percent.
This paper introduces a novel approach for managing 5G millimeter-wave channel switching, addressing the critical need for high-speed, low-latency communication. While promising significantly higher transmission rates, millimeter-wave frequencies are highly susceptible to environmental conditions such as rain, snow, dust, and sand, leading to signal attenuation and connectivity disruptions. To counter these challenges, we propose a Fuzzy Controller for switching mm-wave channels, which utilizes advanced algorithms to ensure smooth and efficient channel transitions. Our model quantifies the impact of environmental conditions on 5G signal propagation, precisely simulating how rainfall influences signal strength. Unlike devices on the market that typically switch between two frequencies based on signal strength alone, our approach intelligently incorporates environmental data such as visibility and rain intensity to choose optimally from five different frequencies. Through extensive simulations and performance evaluations, we show that our approach ensures reliable connectivity while maintaining high data speeds and minimizing latency. This research sets a foundational platform for future investigations into robust millimeter-wave channel switching mechanisms for 5G networks, enhancing user experience and overall network efficiency.
With the rapid growth of electric vehicle (EV) production, efficient battery life cycle management has become increasingly critical, especially as the demand for second-life battery applications is mandated considering environmental aspects. The European Union’s introduction of battery passports, aimed at enhancing battery traceability, presents new challenges for existing Battery Management Systems (BMS). The proposed solution of QR code tracking shows drawbacks when addressing scalability, local real-time monitoring, and data security concerns. Our work implements RFID technology as an extension of modular BMS architectures designed to meet the evolving requirements of battery passports and second-life battery use cases. By integrating NFC tags and leveraging this technology, the system enables secure, real-time data transmission between battery pack components and external readers, overcoming the limitations of QR codes. A demonstrator setup based on automotive-grade components validates the system’s capability to monitor static and dynamic key battery parameters. The proposed solution offers a forward-looking approach to battery management, aligning with upcoming regulatory requirements while advancing the adoption of second-life battery management.
Wireless sensor networks operating on a battery source have limited lifetime and can not be used in extreme environments. Passive sensors on the other hand may operate for a long time even in harsh environmental conditions. Passive sensors are powered using radio frequency waves and reflect a distorted signal transporting the measured parameter that is embedded in the distorted wave. One of the major challenges in such networks is the interference management to support scalability. In this paper, a novel interference mitigation method is proposed, which limits interfering signals at each source preventing their aggregation at the receiver.
This research focuses on the development of a passive X-band cylindrical resonator sensor antenna for temperature sensing applications. The resonator sensor antenna design aims to enable precise and real-time monitoring of temperature while embedded inside various materials and structures like polymers and composites. By integrating the sensing capabilities and a slot antenna directly into the cylindrical resonator structure, the research seeks to minimize additional components and streamline the sensing process. The cylindrical resonator sensor antenna operates at a frequency of 10.6GHz to minimize the size of the resonator and enable high sensitivity and accuracy in detecting subtle changes in Temperature. The cylindrical resonator is made from high-permittivity ceramic-loaded PTFE material by WavePro to ensure minimized dielectric losses and allow for sensor miniaturization. The sensor is interrogated through a high bandwidth probing antenna or a Frequency Modulated Continuous Wave (FMCW) radar and the reflected signals are analyzed to extract resonance data. This study proposes a design for the resonator and antenna through high-fidelity simulations and prototypes ensuring reliable and efficient sensing across a range of industrial and structural applications. The outcomes of this research hold the potential to significantly advance the capabilities of temperature monitoring systems. The novelty of this work resides on (a) using a commercial low-loss dielectric material for sensor implementation, (b) the use of advanced manufacturing techniques including 5-axis femtosecond laser machining, and (c) a novel embedded wireless sensor concept. A linear sensor temperature response is measured in the range of 25-210°C, at a sensing distance of 0.5cm.
This paper presents the MAE model that uses a Masked AutoEncoder (MAE) to enhance the observations from commercial passive Radio-Frequency Identification (RFID) devices. It is crucial to address the common issue of RFID readers failing to collect observations from all their hop channels and antennas due to environmental effects and device limitations. The proposed method examines the inner rationale among observations from various channels and antennas to reconstruct the missing observations, which can significantly improve the performance of downstream applications. The experiment results show that when we collect more than 70% observation in all antennas at all channels, our MAE model can restore 90% of the missing phase with an error of less than 0.1 radians, which is even less than the error caused by thermal noise in an RFID system. Our MAE model’s accuracy in restoring missing data provides a promising future to improve the performance of various RFID applications like localization and motion tracking by providing more complete observations.
This paper proposes a wireless strain sensing system for model helicopter rotor blades using implanted backscatter sensors. Strain measurements from two sensors were continuously collected via dedicated subcarrier frequency backscatter channels. While coherent combining of two IQ streams improved packet error rate (PER) in low-speed rotations, it negatively affected performance at high speeds setting due to Doppler shift. Numerical simulations clarified the degradation mechanism and suggested a practical solution: using a single receiving antenna. This approach was validated through laboratory experiments.
In dense RFID systems, power control is crucial for maintaining communication efficiency and preventing reader-to-reader and reader-to-tag interference. Traditional RFID systems often operate at static power levels, which can lead to communication bottlenecks and inefficient tag reads in dynamic environments. This paper proposes an adaptive power control technique designed to improve RFID sensing performance by dynamically adjusting the transmission power based on environmental conditions, tag distance, and network congestion. Simulations and experimental results demonstrate that the proposed approach improves tag read rates, reduces interference, and enhances system robustness in dense environments.
Our research presents an RFID and IoT-enabled solution for converting sign language into spoken language using deep learning. This tool aims to address communication barriers faced by deaf and mute individuals due to the limited understanding of sign language in the general population. The system employs a hybrid model integrating IoT sensors, RFID technology, and Long Short-Term Memory (LSTM) networks with Transformer architectures. RFID-enabled IoT sensors capture real-time gestures, while Transformer encoders analyze complex contextual relationships between gestures. The LSTM layers handle the temporal aspects of sign movements, enhancing both gesture recognition and contextual understanding. The model, trained on a large dataset of sign language gestures, uses ReLU activation and Adadelta optimization. It achieved a training accuracy of 99%, testing accuracy of 93%, a Recall of 98.76%, a mean Average Precision (mAP) of 98.89%, and a Sensitivity of 97.84%. This innovative approach not only delivers high accuracy but also demonstrates significant potential for real-time sign language interpretation, enabling improved communication accessibility for the deaf-mute community through RFID and IoT technologies.
Radio frequency (RF) fingerprinting is essential for enhancing Physical layer (PHY) security, addressing key challenges in device identification. Feature extractors play a critical role by selecting the most relevant RF fingerprint features, enabling faster and more secure device enrollment. This streamlined enrollment process minimizes reliance on traditional key-based methods, optimizing the system for more efficient data transmission. In our proposed system, built on ISO/IEC 14443 NFC standards, a deep learning model trains the feature extractor to generalize to unseen Proximity Integrated Circuit Cards (PICCs). Focusing on the most relevant features, the system accurately classifies new devices with minimal enrollment data, significantly boosting security.
Physical Layer Security (PLS) has been a long-standing area of research, with Radio Frequency Fingerprinting (RFF) as one of its core components. Recently, the development of Zero Trust Architecture (ZTA) has incorporated RFF to enhance security further. RFF is also used in the Radio Frequency Identification (RFID) field to add another layer of device authentication and security. With advancements in the field of machine learning, RFF technology has benefited from the integration of machine learning techniques. However, several challenges remain unresolved, such as the variation in Channel State Information (CSI), which can significantly impact identification accuracy, particularly in Near Field Communication (NFC) systems. This paper analyzes a channel-robust feature extractor using a ResNet model trained on channel-independent spectrograms. This analysis is conducted within the framework of the ISO/IEC 14443 Type A protocol, a widely used NFC air-interface protocol.
The rapid expansion of Internet of Things (IoT) systems has introduced significant security challenges, particularly for highly resource-constrained edge devices such as battery-powered sensors and UHF RFID tags. Physical Unclonable Functions (PUFs) provide a promising solution for energy-efficient security by generating unique “digital fingerprints” based on device fabrication variations. However, recent advances in Machine Learning (ML) models have shown the ability to compromise the Challenge-Response Pairs (CRPs) of conventional strong PUFs. In contrast, cryptographic algorithms are resilient to ML attacks but lack the intrinsic key that PUFs can provide. In this work, we propose CryptoPUF, a lightweight and ML-resilient hardware solution that integrates a weak PUF with a cryptographic encryption core. CryptoPUF can function as a Crypto-enhanced PUF, adding a security layer to protect the weak PUF from exposure while significantly increasing the number of available CRPs. It also serves as a PUF-enhanced cryptographic encryption core with intrinsic key generation to eliminate the need for on-chip key storage. Evaluation results demonstrate CryptoPUF’s strong resistance to Logistic Regression, Support Vector Machines, and Multilayer Perceptron attacks, achieving a near-ideal 50% prediction accuracy while minimizing hardware resource utilization. Compared to state-of-the-art solutions, CryptoPUF stands out as the most compact ML-resilient PUF, making it a highly efficient and secure option for IoT systems.
14:00 – 14:20
Title: When accuracy counts! Approaches to deploying RFID in highly-regulated manufacturing environments
Contributors: Alessandro Cattaneo; Brendon Parsons; Justin Strait – Los Alamos National Laboratory, USA
Abstract: This workshop will focus on methods for the testing and evaluation of RFID equipment to be deployed in highly-regulated and high-consequence environments. The panelists will direct the discussion to cover topics like building effective mock-up environments, rigorous statistical evaluation of RFID performance, and the design of testing procedures that respect regulatory constraints. The workshop is organized as a roundtable to allow the participants to elaborate on these topics and share their own experiences in the field. The panelists will share their own experience in implementing RFID for nuclear material accountability at Los Alamos National Laboratory. The panelists will highlight strategies they have used to reliably test RFID tags and readers in a “cold” environment, expand on the conclusions they were able to draw from their testing, and provide a retrospective on the cultural change that is triggered by the introduction of a “new” technology. The workshop is aimed at emphasizing statistically-sound design, testing, and modeling principles that can be used transversally across many different industry sectors to evaluate the soundness of RFID products currently available on the market, demonstrate performance against a baseline, and adapt to future RFID offerings in a constantly evolving landscape.
14:20 – 14:40
Contributors: Justin Strait; Alessandro Cattaneo; Brendon Parsons – Los Alamos National Laboratory, USA
Title: Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting
Abstract: Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order hierarchical model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.
14:40 – 15:00
Contributors: Brendon Parsons; Justin Strait; Alessandro Cattaneo – Los Alamos National Laboratory, USA
Title: Statistical Characterization of RFID Tag Performance for Agile Nuclear Material Operations in Cluttered Glove Box Environments
Abstract: The complex propagation of radio frequency (RF) waves in metallic environments such as nuclear material glove boxes complicates the evaluation of radio frequency identification (RFID) performance. While many RFID applications perform highly controlled testing in anechoic RF chambers and translate these results to real-world environments, this approach is challenged by RF reflective environments necessitating testing in realistic environments that approximate the RF characteristics of the application location. We previously constructed an RFID test bed comprising mock glove boxes with dimensions and layouts based on glove boxes and rooms used for nuclear material processing and reported on RFID performance as a function of position within a glove box and proximity to a nearby metal container. In this report we will demonstrate a design of experiments (DoE) approach to comprehensively evaluate RFID performance in a realistic cluttered glove box environment containing variable quantities and sizes of RFID tagged metal containers of a type used in nuclear material processing. The effort developed four different second-order logistic response surface models with decreasing levels of model complexity, ultimately identifying a reduced second-order model that accurately matches the collected data. We will discuss the selected statistical model and the relative performance between three candidate commercial-off-the-shelf (COTS) RFID tags in the context of tag match probability over the entire useful range of RF power for this application. We will also present novel approaches for automating the RFID data collection and improving experimental efficiency, as well as the subsequent benefits of deploying these approaches in nuclear facilities.
This paper proposes the analysis results of the wave propagation for the train position system utilizing the RFID (Radio Frequency Identification) and multiple antenna element. The environment for the wave propagation is the railroad, and the RFID is attached on the bottom of the train. The transmission coefficient was compared whether the concrete bottom existed or not. Due to the multiple reflection, the propagation distance considering the concrete bottom is longer than the one without the bottom. This fact can be utilized for the train detection with RFID attached on the bottom of the train.
With the help of Radio Frequency Identification (RFID) technology, data may be efficiently, automatically, and instantly collected and sent without the need for human participation. This technology has been regarded as a potential solution to lessen issues that jeopardize patient safety or enhance its management. This paper proposes an architecture for the use of RFID in emergency medical services (EMS). The goal of RFID in the proposed architecture is to address problems such as the inadequate medical diagnosis of patients in emergency situations, inadequate identification of incapacitated patients, and inadequate medication administration to patients. All these problems are caused by a lack of patient information, such as their medical conditions and histories or whether they are allergic to certain medications. The security and privacy flaws in the suggested architecture are also covered in this paper, along with recommendations for how to fix them.
Here, we present lightweight, passive, and reconfigurable graphene-based physical unclonable function (PUF) tags used for wireless identification and authentication. The anti-counterfeiting label combines a coil antenna with a graphene quantum capacitor to build an LC oscillator. The variations in the manufacturing processes of graphene give rise to a unique RF response to the reader, which can be enhanced by the existence of a standard PT-symmetric circuit. These RF responses are digitalized into binary encrypted keys. Our simulations illustrate that the proposed graphene-based PUFs can exhibit excellent performance in terms of randomness, uniqueness, and reconfigurability by tuning the gate voltage generated in graphene field-effect transistors (GFETs). Our work can further be applied in security schemes for radio-frequency identification (RFID), near-field communications (NFC), and internet-of-things (IoTs).
The rapid advancement of Internet of Things (IoT) devices has transformed multiple industries. However, the extensive integration of IoT technology has introduced significant security challenges. The physical-layer (PHY) security of IoT devices is vulnerable to malicious hardware modifications, commonly known as hardware Trojans (HTs). Given the unpredictable nature of HTs, there is a need for countermeasures such as radio-frequency fingerprint-based identification methods. This paper presents a novel solution for detecting HTs embedded in wireless devices using millimeter Wave (mmWave) RADAR measurements far outside the operating frequency range of the radar. HT detection using RADAR is demonstrated using a commercial-of-the-shelf mm-wave RADAR, which transmits and receives reflected signals from a passive wireless module designed with a WiFi system-on-chip (ESP8285). The module also includes a custom-made IEEE 802.11 WiFi system-on-chip with signal conditioning components and a hardware Trojan that disrupts the communication link by shorting the antenna. Decision Tree-based model machine-learning approaches are used to successfully identify the presence of HTs from data provided by RADAR measurements, demonstrating their usefulness for large-scale analyses and providing a reliable solution to PHY security challenges. To the best of the authors’ knowledge, this is the first time the concept of using RADAR techniques for hardware trojan detection is presented and validated.