Energy Autonomous UWB Localization

Costanzo, Alessandra; Dardari, Davide; Aleksandravicius, Jurgis; Decarli, Nicolò; Prete, Massimo Del; Fabbri, Davide; Fantuzzi, Marco; Guerra, Anna; Masotti, Diego; Pizzotti, Matteo; Romani, Annalisa

doi:10.1109/jrfid.2018.2792538

Cited by 36 publications

(26 citation statements)

References 63 publications

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“…In the first mode, the unitcells are RF connected and dedicated to short-range communications with multiple tags at different locations. As shown in Figure 3, in this mode, each rectifier is used as an enveloppe detector to demodulate the signal coming from a specific orientation determined by (1) and (2), that can be attributed to a tag. In the second mode, the unitcells are RF isolated and all the rectifiers are connected in series to harvest RF power and convert it into DC power.…”

Section: Rectenna Unitcell's Principlementioning

confidence: 99%

“…For instance, the technique of backscattering has permitted the development of passive radio frequency (RF) identification (RFID) tags, which are the basis of low-power wireless sensor networks in short range communications [1]. In this context, energy harvesting from ambient RF sources or Wireless Power Transfer (WPT) has gained a lot of attention for the energy supply of power-constrained communication networks [1], [2]. Multi-function systems integrating the energy-harvesting function can benefit from a prolonged lifetime and less maintenance.…”

Section: Introductionmentioning

confidence: 99%

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Modular and Reconfigurable Rectenna Unitcells with Beam-Forming Properties

Vandelle

Vuong

Ardila

et al. 2019

2019 49th European Microwave Conference (EuMC)

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This paper presents a modular and reconfigurable rectenna unitcell (RU) made up of an antenna, a rectifier and radiofrequency (RF) power combiners intended to form a scalable and adaptative beam-forming network, for autonomous passive tracking or RFID monitoring applications. The reconfigurable rectenna unitcell allows a dual mode operation thanks to both RF and DC possible combinations of multiple rectenna unitcells. On the one hand, the passive beam-forming operation, coming from the RF combination of multiple rectenna unitcells provides oriented communication or localization capabilities. On the other hand, the series DC connection of RF isolated rectenna unitcells delivers DC power to the system with high output voltage under low RF power densities. Prototypes of 4-edges rectenna unitcells are designed in the 2.4 GHz band. The operation of one individual RU is demonstrated, and it is shown that multiple RUs are suitable for RF energy harvesting, multiple-tag communication and tag localization.

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Section: Rectenna Unitcell's Principlementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modular and Reconfigurable Rectenna Unitcells with Beam-Forming Properties

Vandelle

Vuong

Ardila

et al. 2019

2019 49th European Microwave Conference (EuMC)

View full text Add to dashboard Cite

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“…However, due to the high demand for LBS, significant attention has been made on the development of indoor positioning systems (IPS) recently. Typical ranging techniques based on received-signal-strength-indicator (RSSI) [1], time-of-arrival (ToA) [2], time-difference-of-arrival (TDoA) [3], angle-of-arrival (AoA) [4], and channel-state-information (CSI) [5] have been proposed using various access technologies such as Wi-Fi [6], Bluetooth [7], ultra wide band (UWB) [8], and radio-frequency identification tags (RFID) [9] for indoor positioning. Most ranging techniques require at least three known anchor nodes to calculate the location of the unknown target.…”

Section: Introductionmentioning

confidence: 99%

A Survey of Machine Learning for Indoor Positioning

et al. 2020

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Widespread proliferation of wireless coverage has enabled culmination of number of advanced location-based services (LBS). Continuous tracking of accurate physical location is the foundation of these services, which is a challenging task especially indoors. Multitude of techniques and algorithms have been proposed for indoor positioning systems (IPS's). However, accuracy, reliability, scalability and, adaptability to the environment still remain as challenges for widespread deployment. Especially, unpredictable radio propagation characteristics in vastly varying indoor environments plus access technology limitations contribute to these challenges. Machine learning (ML) approaches have been widely attempted recently to overcome these challenges with reasonable success. In this paper, we aim to provide a comprehensive survey of ML enabled localization techniques using most common wireless technologies. First, we provide a brief background on indoor localization techniques. Afterwards, we discuss various ML techniques (supervised and unsupervised) that could alleviate different challenges in indoor localization including Non-line-ofsight (NLOS) issue, device heterogeneity and environmental variations with reasonable complexity. The trade-offs among multitude of issues are discussed using numerous published results. We also discuss how the ML algorithms can be effectively used for fusing different technologies and algorithms to achieve a comprehensive IPS. In essence, this survey will serve as a reference material to acquire a detailed knowledge on recent development of machine learning for accurate indoor positioning. INDEX TERMS Indoor positioning system (IPS), location-based services (LBS), machine learning (ML), non-line-of-sight (NLOS), wireless positioning, indoor tracking.

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“…Guidi et al 13 implanted a low‐complexity UWB‐RFID system to detect moving tags' position. Also, an UHF/UWB energy‐autonomous tag architecture in Reference 14 is used for simultaneous localization and communication.…”

Section: Introductionmentioning

confidence: 99%

A new UHF/ultra wideband‐radio frequency identification system to solve coexistence issues of ultra wideband‐radio frequency identification and other in‐band narrowband systems

Mir-Moghtadaei

2020

Trans Emerging Tel Tech

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This paper presents a new Ultra Wideband‐Radio Frequency Identification (UWB‐RFID) transceiver to mitigate the coexistence issues of RFID systems and IEEE802.11.a WLAN or other narrowband (NB) systems. The UWB pulse used in the RFID tag is a frequency up‐conversion of the Gaussian pulse first derivative, which has a null in the frequency spectrum. The null is adjusted to be at the center frequency of the WLAN signal, mitigating the mutual interference between RFID and NB systems. In the receiving state, the proposed RFID reader operates in five modes: interference detection, transmitter frequency adjustment by sending commands to the tag, time‐window synchronization, phase and frequency locking, and data reception. During the interference detection mode, the reader serves as a superheterodyne receiver, while it works as an envelope and matched‐filter receiver in the synchronization and locking modes, respectively. In this paper, we show analytically that the reader's frequency in a Phase‐Locked Loop (PLL) can lock on the null frequency of the transmitted signal by the tag. Furthermore, the reader's performance with particular emphasis on PLL and synchronization in the presence of a strong NB interferer is also evaluated. Simulation results demonstrate that the frame synchronization and the phase and frequency lock of the proposed UWB‐RFID transceiver are possible.

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Energy Autonomous UWB Localization

Cited by 36 publications

References 63 publications

Modular and Reconfigurable Rectenna Unitcells with Beam-Forming Properties

Modular and Reconfigurable Rectenna Unitcells with Beam-Forming Properties

A Survey of Machine Learning for Indoor Positioning

A new UHF/ultra wideband‐radio frequency identification system to solve coexistence issues of ultra wideband‐radio frequency identification and other in‐band narrowband systems

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