Pub Date : 2025-07-16DOI: 10.1109/JRFID.2025.3589528
Christopher Saetia;Kaitlyn M. Graves;Serhat Tadik;Gregory D. Durgin
Within the field of radio-frequency identification (RFID) research, tunnel diodes have traditionally been researched for extending backscatter read-ranges for ultra-high-frequency (UHF) RFID tags as reflection amplifiers due to their negative resistance. This same negative resistance can also be used to help construct oscillators. This paper further explores the use of tunnel diodes to make oscillators for harmonic RFID applications and the natural harmonics that arise when biasing these diodes within their negative differential resistance (NDR) regions and with no external injection-locking, interrogating signal from a transmitting source, such as an RFID reader. These harmonics are characterized for five tunnel diode boards, made with the same components, and with each board’s fundamental frequencies’ RF strength measuring at above –15 dBm at a biasing voltage of 200 mV when measured over-the-cable. The best DC-to-RF conversion efficiency achieved in this work was 30%. The occurrence of harmonics from the tunnel diodes creates unique harmonic signatures for each board and demonstrates possible harmonic RFID applications that involve RFID readers discovering and even identifying RFID tags with backscatter-less, hardware-intrinsic, and memory-less IDs generated by such tunnel diodes on these tags. Thus, these harmonic signatures provide alternative or complementary IDs to the traditional IDs stored in tags’ memory.
{"title":"Memory-Less and Backscatter-Less Tunnel Diode Harmonic Signatures for RFID","authors":"Christopher Saetia;Kaitlyn M. Graves;Serhat Tadik;Gregory D. Durgin","doi":"10.1109/JRFID.2025.3589528","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3589528","url":null,"abstract":"Within the field of radio-frequency identification (RFID) research, tunnel diodes have traditionally been researched for extending backscatter read-ranges for ultra-high-frequency (UHF) RFID tags as reflection amplifiers due to their negative resistance. This same negative resistance can also be used to help construct oscillators. This paper further explores the use of tunnel diodes to make oscillators for harmonic RFID applications and the natural harmonics that arise when biasing these diodes within their negative differential resistance (NDR) regions and with no external injection-locking, interrogating signal from a transmitting source, such as an RFID reader. These harmonics are characterized for five tunnel diode boards, made with the same components, and with each board’s fundamental frequencies’ RF strength measuring at above –15 dBm at a biasing voltage of 200 mV when measured over-the-cable. The best DC-to-RF conversion efficiency achieved in this work was 30%. The occurrence of harmonics from the tunnel diodes creates unique harmonic signatures for each board and demonstrates possible harmonic RFID applications that involve RFID readers discovering and even identifying RFID tags with backscatter-less, hardware-intrinsic, and memory-less IDs generated by such tunnel diodes on these tags. Thus, these harmonic signatures provide alternative or complementary IDs to the traditional IDs stored in tags’ memory.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"554-566"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Internet of Things (IoT) has revolutionized Remote Patient Monitoring (RPM) by enabling real-time data transfer. Traditional systems suffer from high energy usage and limited range, making them less suitable for long-term monitoring. This paper presents a novel wearable sensor node leveraging latest Bluetooth Low Energy (BLE) 5.0 features, such as long-range communication and energy-efficient extended advertising. The system integrates an ultra-low-power ARM M33 MCU, a motion sensor for activity tracking, and cloud connectivity for remote monitoring. The Physical Layer (PHY) modes, which determine on-air data transfer, significantly impact communication reliability. Challenges like packet loss are common, especially at extended ranges. Typical solutions involve increasing transmit power or implementing retransmission strategies, each with energy implications. The proposed system pioneers the evaluation of BLE modes–LE 1M and LE Coded PHY–on energy consumption and data transfer reliability of a broadcaster for sensor data transmission in real-time clinical settings. Experimental results reveal that while the conventional LE 1M reduces data transfer time by 84.92%, it increases Packet Loss Rates (PLR). In contrast, the latest LE Coded PHY reduces packet loss to just 2% at ranges upto 300 m but decreases battery life by 42.58%, still allowing a projected 2.6-year lifespan. To address power consumption, we propose a Dynamic PHY Switching Algorithm (DPSA) that adapts PHY modes. Results are validated on an IoT platform, providing insights for selecting BLE PHY for energy-efficient e-healthcare beacons.
{"title":"IoT-Enabled Energy-Efficient and Long-Range Solution for Remote Patient Monitoring Using Bluetooth Low Energy 5.x","authors":"Ridhima Verma;Sukriti Gautam;Navnoor Singh Bal;Suman Kumar;Nagham Saeed","doi":"10.1109/JRFID.2025.3588402","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3588402","url":null,"abstract":"The Internet of Things (IoT) has revolutionized Remote Patient Monitoring (RPM) by enabling real-time data transfer. Traditional systems suffer from high energy usage and limited range, making them less suitable for long-term monitoring. This paper presents a novel wearable sensor node leveraging latest Bluetooth Low Energy (BLE) 5.0 features, such as long-range communication and energy-efficient extended advertising. The system integrates an ultra-low-power ARM M33 MCU, a motion sensor for activity tracking, and cloud connectivity for remote monitoring. The Physical Layer (PHY) modes, which determine on-air data transfer, significantly impact communication reliability. Challenges like packet loss are common, especially at extended ranges. Typical solutions involve increasing transmit power or implementing retransmission strategies, each with energy implications. The proposed system pioneers the evaluation of BLE modes–LE 1M and LE Coded PHY–on energy consumption and data transfer reliability of a broadcaster for sensor data transmission in real-time clinical settings. Experimental results reveal that while the conventional LE 1M reduces data transfer time by 84.92%, it increases Packet Loss Rates (PLR). In contrast, the latest LE Coded PHY reduces packet loss to just 2% at ranges upto 300 m but decreases battery life by 42.58%, still allowing a projected 2.6-year lifespan. To address power consumption, we propose a Dynamic PHY Switching Algorithm (DPSA) that adapts PHY modes. Results are validated on an IoT platform, providing insights for selecting BLE PHY for energy-efficient e-healthcare beacons.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"527-541"},"PeriodicalIF":3.4,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-10DOI: 10.1109/JRFID.2025.3587760
A. B. Barba;N. Panunzio;S. Amendola;G. Marrocco;C. Occhiuzzi
Ensuring precise, in-package monitoring of temperature and relative humidity is fundamental for evaluating drug degradation processes during pharmaceutical Accelerated Predictive Stability (APS) studies. To this purpose battery-less, wireless probe sensors based on Ultra-High Frequency (UHF) Radio Frequency Identification (RAIN RFID) are emerging as innovative solutions for seamless monitoring of the micro-environment inside pharmaceutical packaging. However, APS studies are carried out inside metallic stability chambers that, being reflective, pose significant challenges for RF signal, often leading to reading coverage gaps and inconsistent data. This paper introduces a systematic experimental methodology for designing and validating an optimized multi-antenna RAIN RFID reading architecture for equipping a stability chamber to achieve approximately 100% reading coverage regardless of sensors orientations and positions. By experimentally refining the antenna type, number, and placement, as well as the interrogation power, the proposed methodology reliably overcomes electromagnetic interference. The results underscore the feasibility of robust, high-fidelity data collection via RAIN RFID passive sensors in APS scenarios as finally verified through an extended test for long-term monitoring of temperature and humidity within sealed pharmaceutical containers.
{"title":"A Multi-Antenna RAIN RFID Sensing Architecture for Pharmaceutical Climatic Chambers","authors":"A. B. Barba;N. Panunzio;S. Amendola;G. Marrocco;C. Occhiuzzi","doi":"10.1109/JRFID.2025.3587760","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3587760","url":null,"abstract":"Ensuring precise, in-package monitoring of temperature and relative humidity is fundamental for evaluating drug degradation processes during pharmaceutical Accelerated Predictive Stability (APS) studies. To this purpose battery-less, wireless probe sensors based on Ultra-High Frequency (UHF) Radio Frequency Identification (RAIN RFID) are emerging as innovative solutions for seamless monitoring of the micro-environment inside pharmaceutical packaging. However, APS studies are carried out inside metallic stability chambers that, being reflective, pose significant challenges for RF signal, often leading to reading coverage gaps and inconsistent data. This paper introduces a systematic experimental methodology for designing and validating an optimized multi-antenna RAIN RFID reading architecture for equipping a stability chamber to achieve approximately 100% reading coverage regardless of sensors orientations and positions. By experimentally refining the antenna type, number, and placement, as well as the interrogation power, the proposed methodology reliably overcomes electromagnetic interference. The results underscore the feasibility of robust, high-fidelity data collection via RAIN RFID passive sensors in APS scenarios as finally verified through an extended test for long-term monitoring of temperature and humidity within sealed pharmaceutical containers.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"517-526"},"PeriodicalIF":3.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ambient Backscatter Communication (AmBC) has emerged as a promising low-power wireless communication technique, particularly for Internet of Things (IoT) applications. This paper presents an experimental study on a fifth-generation 5G New Radio (5G-NR) backscatter communication system operating at 3.5 GHz, focusing on bistatic configurations. Specific considerations are taken in the experimental setup to improve signal detection and minimize direct path interference (DPI). For this, a backscatter modulator prototype is developed and tested in controlled environments, including full anechoic (FA) and semi-anechoic (SA) chambers, to analyze its performance under various conditions. Moreover, a generic mathematical model is proposed to predict the power budget of the whole AmBC system. This model takes into account geometrical parameters of the backscatter device (BD), i.e., distance and angles referring to the transmitter (Tx) and the receiver (Rx). The measurement results indicate significant variations in received backscatter power based on environmental factors such as reflections and antenna orientation. Experimental results are in good agreement with the theoretical model, validating the system’s feasibility and highlight the crucial impact of the sensor tag reflections, antenna orientation, and ground absorption on backscattered signal strength. The developed demonstrator consistently reflects a stable signal across different transmit power levels. This study provides key insights into the feasibility of 5G-NR ambient backscatter for energy-efficient wireless communication.
{"title":"Bistatic 5G-NR Ambient Backscatter Communication: Propagation Study and Experimental Validation in Anechoic Chambers","authors":"Mariem Lefki;Moni Sankar Saha;Sahbi Baccar;Moncef Kadi;Hanen Shall;Mohamed Ghorbel","doi":"10.1109/JRFID.2025.3587632","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3587632","url":null,"abstract":"Ambient Backscatter Communication (AmBC) has emerged as a promising low-power wireless communication technique, particularly for Internet of Things (IoT) applications. This paper presents an experimental study on a fifth-generation 5G New Radio (5G-NR) backscatter communication system operating at 3.5 GHz, focusing on bistatic configurations. Specific considerations are taken in the experimental setup to improve signal detection and minimize direct path interference (DPI). For this, a backscatter modulator prototype is developed and tested in controlled environments, including full anechoic (FA) and semi-anechoic (SA) chambers, to analyze its performance under various conditions. Moreover, a generic mathematical model is proposed to predict the power budget of the whole AmBC system. This model takes into account geometrical parameters of the backscatter device (BD), i.e., distance and angles referring to the transmitter (Tx) and the receiver (Rx). The measurement results indicate significant variations in received backscatter power based on environmental factors such as reflections and antenna orientation. Experimental results are in good agreement with the theoretical model, validating the system’s feasibility and highlight the crucial impact of the sensor tag reflections, antenna orientation, and ground absorption on backscattered signal strength. The developed demonstrator consistently reflects a stable signal across different transmit power levels. This study provides key insights into the feasibility of 5G-NR ambient backscatter for energy-efficient wireless communication.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"739-757"},"PeriodicalIF":3.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-07DOI: 10.1109/JRFID.2025.3586561
Md Shakir Hossain;Kyei Anim;Geoffrey Mainland;Kapil R. Dandekar
The convergence of advancements in antenna technology with Machine Learning (ML) is envisioned to enhance coverage and capacity for wireless communication systems in complex and dynamic millimeter-wave (mmWave) indoor environments. These environments often experience significant performance variability due to user movement and obstacles. Our study highlights the potential benefits of combining reconfigurable antenna (RA) systems with ML to address mmWave propagation challenges in indoor environments. However, rigorous verification and validation are essential to ensure accurate modeling of mmWave propagation, which is inherently complex and challenging to evaluate experimentally. To circumvent costly, time-intensive, and non-repeatable real-world measurements, we introduce a hardware emulation framework. It enables realistic evaluation of non-stationary, ray-traced channel models with a large number of propagation paths. This framework integrates realistic channel coefficients from site-specific 3D ray-tracing scenarios with RA-equipped access points (APs) and user mobility features. It incorporates them into a software-defined radio (SDR)-based full-mesh wireless channel emulation system, enabling the coexistence of virtual and real nodes. We present experimental results from transceiver hardware-in-the-loop testing in this testbed. These results feature repeatable and controllable path loss and delays between communicating nodes. Experimental evaluations confirmed that intelligent state selection algorithms, particularly Thompson Sampling and UCB1-Tuned, significantly enhance system performance in terms of throughput and packet error rate, outperforming traditional omni-directional antenna configurations.
{"title":"Toward Realistic SDR-Based Emulation of Ray-Traced Millimeter-Wave Indoor Channels for Next-Generation Wireless Systems","authors":"Md Shakir Hossain;Kyei Anim;Geoffrey Mainland;Kapil R. Dandekar","doi":"10.1109/JRFID.2025.3586561","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3586561","url":null,"abstract":"The convergence of advancements in antenna technology with Machine Learning (ML) is envisioned to enhance coverage and capacity for wireless communication systems in complex and dynamic millimeter-wave (mmWave) indoor environments. These environments often experience significant performance variability due to user movement and obstacles. Our study highlights the potential benefits of combining reconfigurable antenna (RA) systems with ML to address mmWave propagation challenges in indoor environments. However, rigorous verification and validation are essential to ensure accurate modeling of mmWave propagation, which is inherently complex and challenging to evaluate experimentally. To circumvent costly, time-intensive, and non-repeatable real-world measurements, we introduce a hardware emulation framework. It enables realistic evaluation of non-stationary, ray-traced channel models with a large number of propagation paths. This framework integrates realistic channel coefficients from site-specific 3D ray-tracing scenarios with RA-equipped access points (APs) and user mobility features. It incorporates them into a software-defined radio (SDR)-based full-mesh wireless channel emulation system, enabling the coexistence of virtual and real nodes. We present experimental results from transceiver hardware-in-the-loop testing in this testbed. These results feature repeatable and controllable path loss and delays between communicating nodes. Experimental evaluations confirmed that intelligent state selection algorithms, particularly Thompson Sampling and UCB1-Tuned, significantly enhance system performance in terms of throughput and packet error rate, outperforming traditional omni-directional antenna configurations.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"490-506"},"PeriodicalIF":2.3,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A ring-shaped patch antenna is embedded with inductive loads for designing an on-metal tag antenna. Multiple inductive loading structures such as I-shaped patch, C-shaped arms, inductive stubs, and L-shaped stubs have been tactfully integrated into the radiating patch, all on a single layer without requiring additional footprint, for generating sufficient antenna inductance so that the tag resonance can be tuned down to the UHF RFID passband. The proposed tag is planar, and it has a compact size of 50 mm $times $ 50 mm $times 3$ .3 mm. It can achieve good omnidirectional characteristics, maintaining a consistent read range of 11.5 - 12.7 m in the azimuthal plane, due to good impedance matching. The operating frequency of the tag is found to be very stable, and it is not affected much by changes in the backing metal.
环形贴片天线内嵌电感负载，用于设计金属标签天线。多个感应负载结构，如i形贴片、c形臂、感应桩和l形桩已巧妙地集成到辐射贴片中，所有这些都在单层上，而不需要额外的占地面积，以产生足够的天线电感，从而使标签共振可以调谐到UHF RFID通带。所提出的标签是平面的，它的紧凑尺寸为50 mm × 50 mm × 3 mm。由于阻抗匹配良好，可以实现良好的全向特性，在方位面上保持一致的读取范围为11.5 - 12.7 m。发现标签的工作频率非常稳定，并且不受背景金属变化的影响。
{"title":"Ring-Shaped Patch Antenna Embedded With Multiple Inductive Loads for Omnidirectional On-Metal Tag Design","authors":"Subbiah Alagiasundaram;Kim-Yee Lee;Eng-Hock Lim;Pei-Song Chee","doi":"10.1109/JRFID.2025.3586675","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3586675","url":null,"abstract":"A ring-shaped patch antenna is embedded with inductive loads for designing an on-metal tag antenna. Multiple inductive loading structures such as I-shaped patch, C-shaped arms, inductive stubs, and L-shaped stubs have been tactfully integrated into the radiating patch, all on a single layer without requiring additional footprint, for generating sufficient antenna inductance so that the tag resonance can be tuned down to the UHF RFID passband. The proposed tag is planar, and it has a compact size of 50 mm <inline-formula> <tex-math>$times $ </tex-math></inline-formula> 50 mm <inline-formula> <tex-math>$times 3$ </tex-math></inline-formula>.3 mm. It can achieve good omnidirectional characteristics, maintaining a consistent read range of 11.5 - 12.7 m in the azimuthal plane, due to good impedance matching. The operating frequency of the tag is found to be very stable, and it is not affected much by changes in the backing metal.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"466-476"},"PeriodicalIF":2.3,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-07DOI: 10.1109/JRFID.2025.3586807
Lauryn P. Smith;Theodore W. Callis;Marvin Joshi;Genaro Soto-Valle;Denitsa Dimitrova;Fernando Pastrana Aguirre;Manos M. Tentzeris
Millimeter-wave Identification (mmID) is a key enabler for next-generation Internet of Things (IoT) applications. This paper provides a comprehensive review of recent advancements which have improved localization, sensing, and communication through increased read ranges and angular coverages, reduced power consumption, and improved localization accuracies. These advancements are achieved through innovative designs integrating retrodirective arrays, planar and three-dimensional lenses, energy-autonomous solutions, and machine learning techniques. Trade-offs between the different types of mmID tags are discussed and ways of mitigating these challenges are addressed. Additionally, the paper highlights key applications, including wireless sensing, motion tracking for VR/AR applications, structural health monitoring, and high-data-rate backscatter communication. Current limitations and future directions are discussed highlighting the role of machine learning, energy harvesting, and reconfigurable intelligent surfaces (RIS) in advancing next-generation mmID networks. By addressing these factors, this review provides insights into the continued development of mmID technology for widespread adoption in advanced IoT and wireless communication systems.
{"title":"A Comprehensive Review of Millimeter-Wave RFID: Retrodirective Topologies, Passive and Semi-Passive Energy Architectures, and the Integration of Advanced Communication Methods","authors":"Lauryn P. Smith;Theodore W. Callis;Marvin Joshi;Genaro Soto-Valle;Denitsa Dimitrova;Fernando Pastrana Aguirre;Manos M. Tentzeris","doi":"10.1109/JRFID.2025.3586807","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3586807","url":null,"abstract":"Millimeter-wave Identification (mmID) is a key enabler for next-generation Internet of Things (IoT) applications. This paper provides a comprehensive review of recent advancements which have improved localization, sensing, and communication through increased read ranges and angular coverages, reduced power consumption, and improved localization accuracies. These advancements are achieved through innovative designs integrating retrodirective arrays, planar and three-dimensional lenses, energy-autonomous solutions, and machine learning techniques. Trade-offs between the different types of mmID tags are discussed and ways of mitigating these challenges are addressed. Additionally, the paper highlights key applications, including wireless sensing, motion tracking for VR/AR applications, structural health monitoring, and high-data-rate backscatter communication. Current limitations and future directions are discussed highlighting the role of machine learning, energy harvesting, and reconfigurable intelligent surfaces (RIS) in advancing next-generation mmID networks. By addressing these factors, this review provides insights into the continued development of mmID technology for widespread adoption in advanced IoT and wireless communication systems.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"477-489"},"PeriodicalIF":2.3,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-04DOI: 10.1109/JRFID.2025.3585924
Bisma Manzoor;Akram Al-Hourani
The rapid expansion of the Internet of Things (IoT) presents critical challenges in device authentication, network security, and wide-area visibility. While terrestrial solutions have been extensively explored, IoT visibility via Non-Terrestrial Network (NTN) platforms remains underdeveloped, despite the significance of NTN in regions lacking terrestrial communication infrastructure. To address this gap, and accounting for the complexities of satellite communication channel, this work proposes a framework that enables signal-based RF fingerprinting for IoT device classification via satellites by extracting key features from the received signals. The proposed framework integrates MUSIC-based Direction of Arrival (DoA) estimation, a Support Vector Machine (SVM) classifier, and signal processing techniques to extract key RF features, including DoA, modulation type, frequency, and Received Signal Strength Indicator (RSSI). These features are subsequently clustered using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to classify unique transmitters. The results demonstrate high classification accuracy, even under low Signal-to-Noise Ratio (SNR) conditions, providing a scalable solution for IoT device monitoring and spectrum awareness in satellite-based communications.
{"title":"Multimodal RF Fingerprinting for IoT Devices in Satellite-Based Sensing","authors":"Bisma Manzoor;Akram Al-Hourani","doi":"10.1109/JRFID.2025.3585924","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3585924","url":null,"abstract":"The rapid expansion of the Internet of Things (IoT) presents critical challenges in device authentication, network security, and wide-area visibility. While terrestrial solutions have been extensively explored, IoT visibility via Non-Terrestrial Network (NTN) platforms remains underdeveloped, despite the significance of NTN in regions lacking terrestrial communication infrastructure. To address this gap, and accounting for the complexities of satellite communication channel, this work proposes a framework that enables signal-based RF fingerprinting for IoT device classification via satellites by extracting key features from the received signals. The proposed framework integrates MUSIC-based Direction of Arrival (DoA) estimation, a Support Vector Machine (SVM) classifier, and signal processing techniques to extract key RF features, including DoA, modulation type, frequency, and Received Signal Strength Indicator (RSSI). These features are subsequently clustered using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to classify unique transmitters. The results demonstrate high classification accuracy, even under low Signal-to-Noise Ratio (SNR) conditions, providing a scalable solution for IoT device monitoring and spectrum awareness in satellite-based communications.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"507-516"},"PeriodicalIF":2.3,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.1109/JRFID.2025.3584588
Andrei Mogilnikov;Anastasia Lavrenko
This paper provides a comprehensive analysis of recent advancements and ongoing challenges in passive harmonic RFID systems that take advantage of nonlinear operation to enable tracking, sensing, and monitoring in environments where conventional RFID systems fail. The study begins with a detailed review of the literature that highlights key trends and developments in harmonic RFID technology. Then it focusses on chipless harmonic RFID tags that are cost-effective, require no power supply, and operate through nonlinear backscattering, emphasising the main design challenges and limitations. The work further explores methodologies for enabling identification and data transmission in these systems, covering techniques used in tags designed for detection and tracking applications, as well as those meant to function as sensors. Finally, the paper suggests future research directions, emphasising the need for innovations in hybrid system designs, signal processing, and standardisation to improve the scalability and reliability of harmonic RFID systems.
{"title":"Passive Harmonic Transponders With RFID Capabilities: Common Challenges and Techniques","authors":"Andrei Mogilnikov;Anastasia Lavrenko","doi":"10.1109/JRFID.2025.3584588","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3584588","url":null,"abstract":"This paper provides a comprehensive analysis of recent advancements and ongoing challenges in passive harmonic RFID systems that take advantage of nonlinear operation to enable tracking, sensing, and monitoring in environments where conventional RFID systems fail. The study begins with a detailed review of the literature that highlights key trends and developments in harmonic RFID technology. Then it focusses on chipless harmonic RFID tags that are cost-effective, require no power supply, and operate through nonlinear backscattering, emphasising the main design challenges and limitations. The work further explores methodologies for enabling identification and data transmission in these systems, covering techniques used in tags designed for detection and tracking applications, as well as those meant to function as sensors. Finally, the paper suggests future research directions, emphasising the need for innovations in hybrid system designs, signal processing, and standardisation to improve the scalability and reliability of harmonic RFID systems.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"457-465"},"PeriodicalIF":2.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11062612","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-25DOI: 10.1109/JRFID.2025.3583107
Hadi El Hajj Chehade;Bernard Uguen;Sylvain Collardey
This paper introduces comprehensive methodologies for optimizing UHF RFID performance over-the-air. The primary objective is to enhance the effectiveness of UHF RFID tags by maximizing the mean power transmission coefficient and modulation factor, crucial intrinsic characteristics. Through a systematic investigation within a predefined $left ({{sqrt {M},tau }}right)$ , (Q, $gamma $ ) chart, we delve into these attributes, exploring their interplay. For a given chip, we establish and illustrate the valid domain, showcasing optimal antenna impedance choices. The culmination of this process is visually depicted by transforming the chart into the impedance plane, effectively highlighting antenna impedances that concurrently maximize both the mean power transmission coefficient and the modulation factor.
{"title":"Optimizing Antenna Impedance Adaptation for UHF RFID Design","authors":"Hadi El Hajj Chehade;Bernard Uguen;Sylvain Collardey","doi":"10.1109/JRFID.2025.3583107","DOIUrl":"https://doi.org/10.1109/JRFID.2025.3583107","url":null,"abstract":"This paper introduces comprehensive methodologies for optimizing UHF RFID performance over-the-air. The primary objective is to enhance the effectiveness of UHF RFID tags by maximizing the mean power transmission coefficient and modulation factor, crucial intrinsic characteristics. Through a systematic investigation within a predefined <inline-formula> <tex-math>$left ({{sqrt {M},tau }}right)$ </tex-math></inline-formula>, (Q, <inline-formula> <tex-math>$gamma $ </tex-math></inline-formula>) chart, we delve into these attributes, exploring their interplay. For a given chip, we establish and illustrate the valid domain, showcasing optimal antenna impedance choices. The culmination of this process is visually depicted by transforming the chart into the impedance plane, effectively highlighting antenna impedances that concurrently maximize both the mean power transmission coefficient and the modulation factor.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"9 ","pages":"446-456"},"PeriodicalIF":2.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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