Backscatter tags consume extremely low power and are activated by an external carrier for sensing and communication purposes. Analog backscatter tags achieve further power and cost reductions by moving digitization and computation overhead to a remote receiver. Since analog transmissions have a direct mapping to frequency or amplitude, they do not have a digitized frame structure to convey control information such as addresses. Therefore, when multiple tags are deployed it is challenging to identify the tag that transmits the data. We present a novel fully analog tag identification mechanism that is inspired by musical instruments. Each instrument has a unique harmonic content and therefore the human ear can distinguish different musical instruments even when they are playing at the same frequency. By tuning the tags to reflect a unique harmonic content we enable identification of purely analog tags. Our results show that we can create identities for tags by leveraging signal conditioning to modify harmonics, without the need to add dedicated digital blocks for identification purposes. Experiments on our hardware demonstrate that we can successfully identify the tags even in challenging scenarios such as when they are blocked by walls or in motion

This paper describes a simple demodulation technique based on chained, repeating functions for separating and demodulating multiple tags that are simultaneously sending data. When multiple tags transmit simultaneously, the data streams collide often causing data loss. Most protocols detect such collisions and request devices to re-transmit data. However, it is possible to separate the individual tag data streams from the received samples. In a backscatter communication system, all nodes share a common, phase-coherent communication system. This work uses the unique properties of the backscatter channel to receive data from simultaneously-transmitting tags by demodulating received samples in the complex baseband, removing estimates of the received bits from the incoming data stream and continuing further demodulation through repeated application of the demodulation function until all tag transmissions are removed. While similar to recursion, this is a chained, repeating demodulation process and can demodulate several tags that are simultaneously communicating. This paper presents an overview of the signals in a backscatter communication system and measured results from a bench-top over-the-air test using two tags placed 30 cm apart from each other and 1.67 m away from a +27 dBm, 915 MHz reader. The data streams from the two tags fully overlap, but are correctly recovered through the chained, repeated demodulation process.

Digitization is a priority and a key tool to support the development of the Industry 4.0. Many industries, like the automotive sector, rely on complex and costly processes that are still not completely digitized, suffering from poor traceability and limited optimization options due to the lack of proper knowledge of the process internals. In this article we focus on a highly relevant industrial process as part of the automotive assembly line, the painting process, which requires a fine control of the entire cycle temperature without requiring costly operations or complex human interventions. In this article, we propose a novel cost-efficient method for sensing high temperatures with standard UHF RFID sensors. By using low thermal transmission insulation and polynomial models, we achieve to predict temperatures around 200ºC/400ºF with 1.5% error. We believe our proposal opens novel opportunities in the industry to a more cost-efficient fine-grained and process tailored temperature measurement under high temperature conditions.

Recently introduced autotuning RFID ICs can provide digital information on the change in the local boundary conditions in the close surrounding of the tag. By exploiting this feature in combination with a varactor diode, a general framework for the controlled sensing of a chemical agent can be achieved. The varactor acts as a transducer converting the potentiometric output of a chemical sensor into a capacitance change that produces in turn a mismatch between the antenna and the IC. Closed-form expressions relate the digital output of the IC to said chemical variation so that it is well mapped within the retuning dynamic range. The method is demonstrated with reference to a pH sensor and looks promising to provide a sensitivity of 18 units per unitary change of the pH and could be read up to 2 m.

In modern systems that rely on the use of Battery Management Systems (BMS), longevity and the re-use of battery packs have always been important topics of discussion. These battery packs would be stored inside warehouses where they would need to be properly monitored and configured before their re-integration into the new systems. Traditional use of wired connections can be very cumbersome, and sometimes even impossible, due to the outer layers and packaging. To circumvent these issues, we propose an extension to the conventional BMS design that incorporates the use of Near Field Communication (NFC) for the purpose of wireless battery pack status readout. Additionally, to ensure that these packs are only managed by authenticated devices and that the data that is communicated with is protected against outside eavesdropping and tampering, we present a solution in the form of a lightweight security layer on top of the NFC protocol. To show the feasibility of our design, an accompanying prototype has been implemented and evaluated.

Radio Frequency Identification (RFID) improves the efficiency of managing assets in supply chain applications throughout an entire life cycle or while in transport. Transfer of ownership of RFID-tagged items involves replacing information authorizing the old owner with information authorizing the new owner. In this work, we present a two-party, multiple tag, single owner protocol for ownership transfer: 2P-mtOTP. This two party protocol depends only on the communication among the two owners and the tags. Further, 2P-mtOTP is robust to attacks on its security, and it preserves the privacy of the owners and tags. We analyze our work in comparison to recent ownership transfer protocols in terms of security, privacy, and efficiency.

RFID-tagged items can change owners at different points, for example, when a retail item is purchased or as part of a supply chain. Ownership transfer (OT) is to give the new owner a level of privileged access to the RFID tag by establishing secrets shared by new owner and tag, replacing the access and secrets of the old owner. Some OT protocols employ a trusted third party (TTP) as intermediary between old and new owners to protect the privacy of each from the other. In this paper, we present an OT protocol, TTP-mtOTP, to transfer multiple tags from an old owner to a new owner, using a TTP. In the protocol, the TTP provides information for a tag that belongs to the old owner to be able to recognize that a transfer is authorized and to authenticate the new owner. We establish the old and new owner privacy as well as the resistance of TTP-mtOTP against multiple security attacks. We compare privacy, security, computation, and communication properties of TTP-mtOTP against those of other OT protocols for multiple tags that use a TTP.

We propose a collision recovery algorithm with the aid of machine learning (ML-aided) for passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) systems. The proposed method aims at recovering the tags under collision to improve the system performance. We first estimate the number of tags from the collided signal by utilizing machine learning tools and show that the number of colliding tags can be estimated with high accuracy. Second, we employ a simple yet effective deep learning model to find the experienced channel coefficients. The proposed method allows the reader to separate each tag's signal from the received one by applying maximum likelihood decoding. We perform simulations to illustrate that the use of deep learning is highly beneficial and demonstrate that the proposed approach boosts the throughput performance of the standard framed slotted ALOHA (FSA) protocol from 0.368 to 1.837, where the receiver is equipped with a single antenna and capable of decoding up to 4 tags.

A method of detecting UHF RFID tags with SQL injection virus code written in its user memory bank is explored. A spectrum analyzer took signal strength readings in the frequency spectrum while an RFID reader was reading the tag. The strength of the signal transmitted by the RFID tag in the UHF range, more specifically within the 902-908 MHz sub-band, was used as data to train a Random Forest model for Malware detection. Feature reduction is accomplished by dividing the observed spectrum into 15 ranges with a bandwidth of 344 kHz each and detecting the number of maxima in each range. The malware-infested tag could be detected more than 80% of the time. The frequency ranges contributing most in this detection method were the low (903.451- 903.795 MHz, 902.418-902.762 MHz) and high (907.238-907.582 MHz) bands in the observed spectrum.

This paper investigates a low-cost implementation of a UHF-RFID portal enhanced by artificial intelligence to assess whether a tag is crossing the portal or it is static in the surrounding. The reference scenario concerns anti-theft systems in fashion stores, where the use of shielded RFID portals is not feasible and spurious tag readings must be filtered by alternative methods. The portal consists of a commercial RFID reader connected to an array antenna placed at the store entrance to monitor the tag crossing. Data processing involves Received Signal Strength Indicator sequences and a comparison among Support Vector Machine (SVM) and several LSTM (Long Short-Term Memory) neural networks investigated to perform classification. System and algorithm validation are conducted through an experimental analysis.

Transport package test represents the integrity check of packaged commercial products exposed to an emulated transportation environment such as vibrations and shocks. This paper examines the practicality of wireless transport package test with a backscatter streaming system with battery-free backscatter sensors by extensive experiments. The system bases on Gen2 protocol with a set of streaming extensions. Random vibration and drop tests, defined in an ISO standard, were performed on a test subject PC. The measurement accuracy of the backscatter streaming system was compared with that of wired sensor to reveal that the accuracy of the system is sufficient for basic transport package test conditions. It was confirmed that the wireless, battery-less and lightweight natures of the backscatter sensor facilitate the test preparation and configuration changes, and is advantageous in continuous wireless streaming. In addition to the merits, the limitations of the system in transport package test are also discussed.

Radio Frequency Identification (RFID) technology improves service quality in inventory management, behavior analysis, etc. Tracking the movement of Passive RF tags is the challenging application in these services. As the first step, the direction estimation scheme for RF tags has attracted attention. Conventional estimation schemes have some issues due to ample space for antenna installation or expensive phased array antennas. As a result, implementation is challenging for the actual field, such as warehouses or stores. This paper proposes a state estimation scheme for multiple RF tags with an angled antenna. Since the proposed scheme learns various parameters such as RSSI, Phase angle values, etc., it can estimate three states: stay, forward and backward direction as the RF tags' state. The evaluation results show the estimation accuracy with different combinations of learning parameters.

The article describes the course of research of a R&D project to develop a chamber for the separation of reading a UHF RFID multiple tags in a dense environment. The necessity to apply the developed solution resulted from the operational conditions of the national postal operator in Poland. During the pilot implementation of the UHF RFID system on the gates of distribution centers, it was found that in order to identify the inhomogeneous content of pallet loading units, containing up to 200 different packages of unknown content, it will be necessary to build a solution that allows the use of the maximum radiation power of the reader with simultaneous radio separation from the environment. At the same time, the developed solution uses the phenomenon of electromagnetic wave reflections, generated by the metal housing of the scanning chamber, to eliminate dead areas and the adverse interaction of a significant number of tags contained in the collective packaging. The developed solution made it possible to obtain practically 100% efficiency of reading the tagged parcels with the simultaneous full automation of the inventory process.

This paper presents a ray tracing based channel simulation for the evaluation of ultra-high-frequency (UHF) radio-frequency identification (RFID) ranging methods. In order to account for the diffuse multipath (DM) of an indoor channel, the ray tracer is extended by a statistical model. For the range estimation, a matched filter (MF) and a maximum likelihood (ML) estimator are implemented. The latter exploits the use of multiple-input-multiple-output (MIMO) information. The estimators are evaluated with respect to both the simulated channel model and the data from a measurement campaign. It is shown that the results provided by the simulations and the measurements agree to a large extent. This nominates the presented channel simulation as an efficient method for the evaluation of indoor localization systems.

A new M-shaped UHF RFID tag on metal with a compact footprint of 40 mm × 24 mm × 1.1 mm (0.122λ × 0.073λ × 0.003λ at 915 MHz) is proposed. The antenna consists of an M shaped patch and a ground plane. The tag antenna can be easily fabricated on a thin flexible PET sheet substrate. It is fabricated by folding the flexible substrate, and the structure is simple. It has 3 design parameters and can achieve different degrees of conjugate matching. By changing the parameters, the impedance can be easily adjusted and the resonant frequency of the antenna can be changed finely. An equivalent circuit is built to estimate the input impedance of the antenna. The results show that the impedance conjugate matching between the tag antenna and the chip can be easily achieved by using the M shaped feeder. In the simulation, the antenna has a high power transmission coefficient (~1). With an effective isotropic radiated power (EIRP) of 4 W, the tag can achieve a long reading distance of 6.9 m on metal surfaces.

In this paper, the design of a high gain circular polarization (CP) radio frequency identification (RFID) reader antenna for the ultra-high frequency (UHF) band is described. The antenna is designed with a 2 × 2 array configuration by applying the sequential rotation technique, which guarantees excellent axial ratio (AR) performance and high gain. Furthermore, in order to maximize the antenna gain, both the height of the CP antenna elements and the antenna element arrangement have been optimized. In addition, the two-level series power divider based feed network central element has been opportunely rotated to minimize the feed network insertion loss. A CP gain larger than 14.6 dBic with a 600 × 600 mm2 antenna array has been measured within the FCC bandwidth 902-928 MHz, with outstanding impedance matching and AR performance.

Radio astronomy and other passive radio spectrum users have significant challenges avoiding interference from wire- less communication systems. Even distant transmitters sometimes interfere with passive users. We propose Pseudonymetry, a system that provides (primary) passive users a means to turn off the transmissions of the particular (secondary) wireless transmitter that interferes with it. By controlling the specific transmitter rather than an entire geographical region, Pseudonymetry could increase the spectrum available for wireless systems while en- suring rapid clearing of interferers as necessary for passive use. Pseudonymetry adds a low rate watermark to the secondary (intended) transmitted signal to carry a random, anonymous pseudonym. We show the ability of a passive receiver to decode the watermark, even from a signal received with very low SNR. The passive receiver posts to a centralized database to provide feedback to the secondary transmitters so that they know to vacate the band. We provide analysis that captures the trade-offs in the design of Pseudonymetry, and show initial evidence that a simple amplitude modulation watermarking scheme could enable reliable detection at a distant passive receiver, while resulting in minimal degradation to the error performance of the intended secondary receiver.

A novel on-chip carrier leakage suppression receiver front-end with low noise figure and high sensitivity for ultrahigh-frequency (UHF) radio frequency identification (RFID) reader is proposed exploring a low-noise transconductance amplifier (LNTA)-first architecture. A 4-path passive mixer and a LNTA are adopted to transfer the baseband band-pass property to the mixer and receiver input and form a band-stop input impedance. As a result, the obvious impedance and gain difference between in-band and carrier signal is the key to achieving leakage suppression. Furthermore, the gain of the LNTA can effectively minimize the noise contribution from subsequent stages of the receiver to reduce noise figure and improve sensitivity. Implemented in a 55nm CMOS process, the noise figure of the LNTA-first receiver front-end is 15.7dB at the offset frequency of 600kHz, which is 4.2dB lower than the mixer-first, so the sensitivity is improved. Furthermore, the carrier leakage rejection ratio is 51dB, which is 1.5dB higher than the mixer-first. The results indicate that the LNTA-first receiver is more promising than the mixer-first in NF and sensitivity without sacrificing leakage suppression for UHF RFID applications.

This paper describes an all-digital backscatter modulation approach leveraging delta-sigma modulation (DSM) to improve the in-channel spectral characteristics of orthogonal frequency division multiplexed (OFDM) backscatter communication. We demonstrate through numerical simulations and experimental validation that DSM can improve the spurious-free dynamic range (SFDR) of OFDM subcarriers generated by a low-resolution impedance digital-to-analog converter (DAC), such as an RF switch having two or four different impedance states. We present the design and validation of a prototype OFDM backscatter uplink with DSM implemented with all-digital logic in an FPGA. A single-pole-four-throw CMOS RF switch (i.e. 2-bits of impedance DAC resolution) serves as the backscatter modulator. We experimentally validated the DSM approach with a 2.4 GHz, five-subcarrier OFDM backscatter uplink and a four-times oversampling DSM at up to 1.25 Mbps. In this scenario, the DSM improved the SFDR by 4.3 dB within the subcarrier band while reducing the overall noise floor in the same band by 11.3 dB. These results confirm that a DSM approach can be used to control quantization noise and improve the spectral characteristics of low-resolution digital impedance modulators for backscatter communication in scenarios where in-channel SFDR is more important than wideband noise performance.

We present an all-digital application specific integrated circuit (ASIC) that implements Bluetooth Low Energy (BLE)-compatible backscatter communication. The ASIC was fabricated in a 65nm CMOS process and occupies active area of 0.12mm^2 while consuming a total of 205 uW of power from 0.48~V and 1~V supplies. Of the total power consumption, 56% (115uW) is consumed by the digital logic, 16% (33uW) by the oscillator, and 28% (57uW) by the RF switch used as a backscatter modulator. The ASIC broadcasts up to 1000 packets/sec BLE advertising packets at 1 Mbps, yielding a backscatter modulator efficiency of 57 pJ/bit. The device was validated in both cabled and wireless measurements setups, demonstrating compatibility with unmodified smartphones as well as commercially available BLE chips, such as the Nordic Semiconductor nRF51822. With the wireless test setup used in this work, the ASIC has a theoretical maximum read range of 4.9 m using a smartphone. Building off previous work in BLE backscatter communication using FPGA-based prototypes, this work provides an important quantitative demonstration of the size and power savings that can be achieved in a BLE-compatible backscatter ASIC.

In this paper, a new asymmetrical triple-mode resonator that can be used in chipless radio frequency identification (RFID) tags is introduced. The proposed resonator is constructed by locating two open-circuited stubs in different electrical length to an open loop resonator. Two resonant frequencies can be controlled by these asymmetrical stubs, while the main resonant frequency is resulted from the nature of the open loop resonator. It is proven that the proposed resonator can allow obtaining 5 frequency codes from a single triple-mode resonator. A multi-resonator circuit is also designed by coupling 6 triple-mode resonators to a bended transmission line which connects input to output port. For the experimental verifications, three circuits having different frequency code combinations have been fabricated and measured in an excellent agreement with the simulated results. Totally 18 resonant frequencies resulted from the 6 triple-mode resonators have been clearly observed in the measurements. The proposed multi-resonator circuit can be utilized for chipless RFID tags and 56 frequency codes can be generated.

Long-Range (LoRa) is a low-power wide-area (LPWA) technology which is nowadays the pillar of many IoT (internet of things) systems worldwide. Among the multiple applications that LoRa can enable, the search and rescue (SaR) in the harshest environments wherein standard radiofrequency technologies cannot establish communications is gaining attention. Wearable LoRa radios can significantly foster SaR operation so that the survival chances of the target person increase dramatically. After introducing the international research trend, this contribution reviews the advances on the topic achieved by the Pervasive Electromagnetics Lab of the Tor Vergata University of Rome. The incredibly challenging case of mountain SaR operations was investigated, highlighting how the LoRa-based wireless localization can enable a new generation of SaR devices, significantly outperforming the current systems.

This work presents a phase-based device-free localization (DFL) scheme for tracking the movement of a human target by employing a network of anchor RFID tags inside the search space. The proposed method measures the phase disturbances of the backscattered field induced by a target roaming in the propagation environment and detects whether an antenna-to-tag link is obscured or not. This binary information is fused by a geometrical model that realises the target as a cylinder, thanks to which the position of the target can be identified even by a single reader-antenna. A particle filter algorithm (PF) keeps track of the target's movement over time, smoothing otherwise abrupt maneuvers. Experimental results with a single antenna report a median absolute localization error in the order of 20cm which decreases to 15cm when more antennas are employed. The real-time capability of the method is also verified.

Resistive Random Access Memory (RRAM) is a process and voltage compatible embedded nonvolatile memory- with high density. The interest in RRAM is increasing due to the growing impact of the von Neumann bottleneck on current memory technologies like DRAM and SRAM. RRAM's density is similar to that of DRAM, while only consuming a fraction of the power. However, as a developing technology, many of its features are uncharacterized, including its fault rate. In this paper, we characterize the factors influencing the initial fault rate of RRAM as well as an experimental method for its mitigation, and an overall fault rate reduction of 1516.4 times from previous literature.

Localization based on signals from cellular base stations (BSs) or WiFi access points is important particularly in urban environments where street canyon effects impair GPS reception. A popular implementation is based on fingerprinting, where associations between channel characteristics and location of a user equipment (UE) are measured in a training phase, and later (in the testing of operating phase) used to localize a UE measuring a particular channel. This paper considers the combination of labeled and unlabeled channel state information (CSI) for such finger-printing based localization, in particular to account for the fact that moving objects like cars can change the CSI between training and testing. To enhance the robustness of the localization against these and other ''unseen" scenarios, we propose a solution approach based on a deep domain adaptation (DA) framework. The proposed method contains an unsupervised domain adaptation regression and an adversarial training module. The first component aims to learn discriminative fingerprinting representations jointly with data collected from seen and unseen scenes. The second one alleviates the distribution divergence of fingerprints collected from seen and unseen scenes, which eventually enables effective knowledge transfer. We evaluate the performance of the proposed method in a challenging setup, the recently released dynamic scenario in the DeepMIMO dataset. The results demonstrate that the proposed method can provide robust and accurate location estimation over variable numbers of the time-varying scenarios, with superior performance over other compared methods.

UHF-RFID Synthetic Aperture Radar (SAR) Robotic-based localization and inventory systems are now widespread in literature. As known from the SAR theory, the tag localization accuracy along a given spatial direction depends on the antenna motion along the same direction. Indeed, the overall accuracy of the system depends on its capability to also determine the height from the floor of the RFID tag. This paper proposes a comparison between exploiting two antennas at different fixed heights or a single moving antenna hooked to a handling system that describes a vertical motion to localize the tag in the 3D space. The accuracy of the system is investigated with respect to the Signal-to-Noise-Ratio and a discussion on design criteria for the best system is given.

Reflections from objects can interfere with RFID localization. This work offers a method for the joint estimation of reflectors' and tags' locations, without any prior knowledge. When block coherence is relatively small and wall reflection relatively strong, the method localizes the tag and the wall/reflector with impressive accuracy, in the order of $5$ cm. Narrowband measurements, spread in space can improve the performance of the algorithm, which is important for narrowband UHF RFID. Experimental results also indicate cases where the performance of the method degrades. Hopefully, this work will spark interest on ``classifying'' the environment as line-of-sight or multipath-rich, discovering the order of reflections for the latter case.

A new phase-based localization method for RFID is proposed. The position of a target tag is determined relative to a minimum of 3 reference tags of know locations using phase measurements of the target tag and reference tags along 2 straight trajectories. Experiments show a 2D mean localization error is around 12 cm. Compared to other methods, few reference tags are required, and the only trajectory information required is the distance along the track where phase readings are recorded.