UHF RFID Channel Emulation Testbed for Wireless IoT Systems

Tajin, Abu Saleh; Jacovic, Marko; Dion, Geneviève; Mongan, William M.; Dandekar, Kapil R.

doi:10.1109/access.2021.3077845

Cited by 6 publications

(2 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various numbers and types of devices under test, jammers, physical environments, and levels of mobility may be considered. In addition to jamming, we have used the ray‐tracing emulation system to examine Ultra‐high‐frequency (UHF) Radio Frequency Identification (RFID) for wireless IoT devices, thus highlighting the versatility of the system [65]. The overall workflow we described is suitable for other channel emulator systems and may be extended for compatible scenario development.…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

Experimentation framework for wireless communication systems under jamming scenarios

Jacovic

Liston

Pano

et al. 2022

IET Cyber-Phy Sys Theory & Ap

Self Cite

View full text Add to dashboard Cite

Cyber-physical systems (CPS) integrate control, sensing, and processing into interconnected physical components to support applications within transportation, energy, healthcare, environment, and various other areas. Secure and reliable wireless communication between devices is necessary to enable the widespread adoption of these emerging technologies. Cyber-physical systems devices must be protected against active threats, such as Radio Frequency (RF) Jammers, which intentionally disrupt communication links. Jamming detection and mitigation techniques must be evaluated extensively to validate algorithms prior to full implementation. Challenges related to obtaining zoning permits, Federal Aviation Administration (FAA) pilot certification for Unmanned Aerial Vehicles (UAVs), and Federal Communications Commission (FCC) licencing lead to evaluation limited to simulation-based or simplistic, non-representative hardware experimentation. A site-specific ray-tracing emulation framework is presented to provide a realistic evaluation of communication devices under RF jamming attacks in complex scenarios involving mobility, vehicular, and UAV systems. System architecture and capabilities are provided for the devices under test, real-world jamming adversaries, channel modelling, and channel emulation. Case studies are provided to demonstrate the use of the framework for different applications and jamming threats. The experimental results illustrate the benefit of the ray-tracing emulation system for conducting complex wireless communication studies under the presence of RF jamming. K E Y W O R D Scyber-physical systems, hardware-in-the-loop stimulation, telecommunication security | INTRODUCTIONWith the emergence of new wireless technologies in our everyday lives, such as in Cyber-Physical Systems (CPS), Vehicular, Unmanned Aerial Vehicle (UAV) communications, and the Internet of Things (IoT), protecting devices against external threats is essential for society to thrive in the future. Cyber-Physical Systems in particular has a high dependence on communication systems for data and control, leading to vulnerabilities to attacks [1]. Radio frequency (RF) jammers disrupt the wireless RF medium by transmitting signals with the malicious intent to interfere with legitimate communication systems. In critical communication systems, for instance, autonomous vehicles, medical device readings, and mobile access points for disaster relief, the consequences can be catastrophic.Types of RF jammers include constant, random, intermittent, reactive, and intelligent [2]. The constant jammer is straightforward in operation, sending a jamming signal at a centre frequency with a given bandwidth. The continuous nature of the threat results in simple detection and inefficient energy usage; therefore, more complex jammers are implemented. Random jammers trigger a jamming event with a set probability; similarly, intermittent jammers operate in setThis is an open access article under the terms of the Creative Commons Attribution License, which permi...

show abstract

Section: Discussion and Future Directionsmentioning

confidence: 99%

Experimentation framework for wireless communication systems under jamming scenarios

Jacovic

Liston

Pano

et al. 2022

IET Cyber-Phy Sys Theory & Ap

Self Cite

View full text Add to dashboard Cite

show abstract

“…We have used this framework previously for a medical Internet-of-Things application in ref. [40] and have extended its use for RF jamming studies in ref. [22].…”

Section: Ray Tracing Emulationmentioning

confidence: 99%

Mitigating RF jamming attacks at the physical layer with machine learning

Jacovic

Rey

Mainland³

et al. 2022

IET Communications

Self Cite

View full text Add to dashboard Cite

Wireless communication devices must be protected from malicious threats, including active jamming attacks, due to the widespread use of wireless systems throughout our everyday lives. Jamming mitigation techniques are predominately evaluated through simulation or with hardware for very specific jamming conditions. In this paper, an experimental software defined radio-based RF jamming mitigation platform which performs online jammer classification and leverages reconfigurable beam-steering antennas at the physical layer is introduced. A ray-tracing emulation system is presented and validated to enable hardware-in-the-loop jamming experiments of complex outdoor and mobile site-specific scenarios. Random forests classifiers are trained based on over-the-air collected data and integrated into the platform. The mitigation system is evaluated for both over-the-air and ray-tracing emulated environments. The experimental results highlight the benefit of using the jamming mitigation system in the presence of active jamming attacks. INTRODUCTIONWireless communication systems exist widely throughout commercial, industrial, military, and consumer domains. Communication links must be reliable and well-protected from external threats, in particular for medical and vehicular applications, which are critical to human well-being and safety. Radio frequency (RF) jammers intentionally disrupt the RF medium with active attacks to maliciously impact the performance of legitimate communication devices. Mitigation techniques in the presence of jamming have predominately been evaluated in the past through theoretical and simulation based studies [1-7].Recent approaches have leveraged neural networks [8] and reinforcement learning [9][10][11][12] to circumvent the effects of a jammer. In all of the aforementioned studies, analysis was limited to simulation and would benefit from experimental evaluation to provide a greater sense of realism to the communication devices considered. Hardware-based systems have focused on performing jamming mitigation primarily for lowrate hostile military applications [13,14] or for very specific jammer types [15,16]. A more generalised solution must beThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

A 22-m Operation Range Semi-Passive UHF RFID Sensor Tag With Flexible Thermoelectric Energy Harvester

et al. 2022

View full text Add to dashboard Cite

This paper presents a wireless temperature sensor tag able to work in both fully passive mode and in semipassive mode when assisted by a flexible thermoelectric generator (TEG). The sensor tag consists of an EPC C1G2/ISO 18000-6C Ultra-high frequency (UHF) radiofrequency identification (RFID) integrated circuit (IC) connected to a low power microcontroller unit (MCU) that samples and collects the temperature from a digital temperature sensor. With a temperature gradient as low as 2.5 ºC, the test results show that the TEG provides an output power of 400 µW with an output voltage of 40 mV. By means of an up-converter in order to boost the TEG output volt age, this harvester supplies the power required to the sensor tag for a 2 conv/s data rate in semipassive mode. Moreover, when the tag operates in semi-passive mode, a communication range of 22.2 m is measured for a 2 W effective radiated power (ERP) reader. To the authors' knowledge, the proposed TEG-assisted sensor tag shows the longest communication range and the only that provides stable external power at low temperature gradients. The measured performance and the chosen architecture allow using the wireless sensor in multiple industrial or biomedical applications.

show abstract

UHF RFID Channel Emulation Testbed for Wireless IoT Systems

Cited by 6 publications

References 25 publications

Experimentation framework for wireless communication systems under jamming scenarios

Experimentation framework for wireless communication systems under jamming scenarios

Mitigating RF jamming attacks at the physical layer with machine learning

A 22-m Operation Range Semi-Passive UHF RFID Sensor Tag With Flexible Thermoelectric Energy Harvester

Contact Info

Product

Resources

About