Multi-reader multi-tag architecture for UWB/UHF radio frequency identification systems

Alesii, Roberto; Marco, Piergiuseppe Di; Santucci, F.; Savazziy, Pietro; Valentini, Roberto; Vizziello, Anna

doi:10.1109/eurfid.2015.7332381

Cited by 14 publications

(6 citation statements)

References 12 publications

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“…Indeed, if the interrogation areas decoupling is guaranteed, the multi-reader scenario can be analyzed as a superimposition of four independent single-reader systems. Furthermore, the reader-to-tag synchronization scheme proposed in [1] can be applied in the multi-reader scenario.…”

Section: Enhanced Q-algorihmmentioning

confidence: 99%

“…The reader despreads the received UWB backscattering signal r(t), with reader code d n and UWB group tag codes d g m according to (1) and (14) and identifies the empty/busy groups.…”

Section: Uwbanduhf-cs Algorithm First Step: Estimating the Number Of K mentioning

confidence: 99%

“…The reader first energizes passive tags by means *Correspondence: roberto.alesii@univaq.it This paper has been presented in part in the EURASIP RFID Workshop, Rosenheim, 22-23 October 2015 [1] 1 Centre of Excellence DEWS, University of L'Aquila, via Vetoio snc, Coppito, 67100 L'Aquila, Italy Full list of author information is available at the end of the article of electromagnetic energy and then identifies the objects by collecting unique IDs stored in the tag's memory.…”

Section: Introductionmentioning

confidence: 99%

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Backscattering UWB/UHF hybrid solutions for multi-reader multi-tag passive RFID systems

et al. 2016

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Ultra-wideband (UWB) technology is foreseen as a promising solution to overcome the limits of ultra-high frequency (UHF) techniques toward the development of green radio frequency identification (RFID) systems with low energy consumption and localization capabilities. While UWB techniques have been already employed for active tags, passive tags solutions are more appealing also due to their lower cost. With the fundamental requirement of maintaining backward compatibility in the RFID domain, we propose a hybrid UWB/UHF architecture to improve passive tag identification both in single-reader and multi-reader scenarios. We then develop two hybrid algorithms: the first one exploits the UWB signal to improve ISO/IEC 18000-6C UHF standard, while the other one exploits UWB to enhance a compressive sensing (CS) technique for tag identification in the multi-reader, multi-tag scenario. Both solutions are able to improve success rate and reading speed in the tag identification process and reduce the energy consumption. The multi-reader version of the proposed approaches is based on a cooperative scheme in order to manage reader-tag collisions and reader-reader collisions besides the typical tag-tag collisions. Furthermore, timing synchronization non-idealities are analyzed for the proposed solutions and simulation results reveal the effectiveness of the developed schemes.

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Section: Enhanced Q-algorihmmentioning

confidence: 99%

“…The reader despreads the received UWB backscattering signal r(t), with reader code d n and UWB group tag codes d g m according to (1) and (14) and identifies the empty/busy groups.…”

Section: Uwbanduhf-cs Algorithm First Step: Estimating the Number Of K mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Backscattering UWB/UHF hybrid solutions for multi-reader multi-tag passive RFID systems

et al. 2016

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“…Furthermore, proper transmission techniques suitable for intra-body may be designed, leveraging on the channel model findings, including UWB, compressive sensing trasmission methods [38], and simple digital modulation schemes [39], appropriate for implanted transceivers. Also, multiple implants scenario are conceived, in which it is fundamental to develop opportunistic wake-up methods with location awareness of devices [40]- [42] or to exploit resource allocation methods [43] to minimize energy consumption as required in IBNs.…”

Section: A Channel Modeling and Transceiver Designmentioning

confidence: 99%

Experimental Channel Characterization of Human Body Communication Based on Measured Impulse Response

Vizziello¹,

Savazzi²,

Dell’Acqua³

2023

Preprint

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<p>The emerging research area of intra-body communication (IBC) will foster personalized medicine by enabling interconnection of implanted devices that ensure pervasive patient monitoring and characterization. Communication takes place through energy-efficient technologies such as the capacitive coupling (CC) and galvanic coupling (GC) techniques, which enable body-area communication without wiring; however, the relative novelty of such communication methods means their modeling is still incomplete. This paper focuses on channel characterization of the human body, directly comparing for the first time CC and GC techniques in both wearable and implantable configuration. Experimental data are considered to evaluate the measured impulse response in both ex-vivo chicken tissue and in-vivo human tissue in a frequency range up to 100 kHz. Pseudorandom noise (PN) sequences are transmitted in baseband and a correlative channel sounding system is implemented to evaluate the channel impulse and frequency response through real measurements. Experimental results demonstrate that the channel is relatively flat in the frequency range of interest, which simplifies the design of a transceiver suitable for intra-body networks (IBNs).</p>

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“…Where, the B si 1,2 is the summation of l 2 norm of each row in B si [5]. The aforementioned optimization problem can be formulated for joint channel estimation at BS [30], as shown in equation (17) min…”

Section: A Comparison Of Dictionary and Dft Basis For Measurement Mamentioning

confidence: 99%

Joint Sparse Channel Recovery With Quantized Feedback for Multi-User Massive MIMO Systems

et al. 2020

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Accurate channel state information (CSI) at the transmitter is an essential prerequisite for transmit beamforming in massive multiple input multiple output (MIMO) systems. However, due to a large number of antennas in massive MIMO systems, the pilot training and feedback overhead become a bottleneck. To resolve this issue, the research work presents a novel framework for frequency division duplex (FDD) based multiuser massive MIMO system. A 2-step quantization technique is employed at the user equipment (UE) and the CSI is recovered at the base station (BS) by applying the proposed compressed sensing (CS) based algorithms. The received compressed pilots are quantized by preserving 1 bit per dimension direction information as well as the partial amplitude information. Subsequently, this information is fed back to the BS, which employs the proposed quantized partially joint orthogonal matching pursuit (Q-PJOMP) or quantized partially joint iterative hard thresholding (Q-PJIHT) CS algorithms to recover the CSI from a limited and quantized feedback. Indeed, an appropriate dictionary and the hidden joint channel sparsity structure among users is exploited by the CS methods, resulting in the reduction of the feedback information required for channel estimation. Simulations are performed using singular value decomposition (SVD) and minimum mean square error (MMSE) beamforming utilizing the estimated channel. The results confirm that the proposed 2-step quantization approaches the system with channel knowledge without quantization, thus overcoming the training and feedback overhead problem. Moreover, the proposed 2-step quantization outperforms 1-bit quantization, at the cost of slightly higher complexity. INDEX TERMS Compressed sensing, joint channel estimation, quantization, channel state information (CSI), multiple input multiple output (MIMO), sparse channel estimation, dictionary.

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Multi-reader multi-tag architecture for UWB/UHF radio frequency identification systems

Cited by 14 publications

References 12 publications

Backscattering UWB/UHF hybrid solutions for multi-reader multi-tag passive RFID systems

Backscattering UWB/UHF hybrid solutions for multi-reader multi-tag passive RFID systems

Experimental Channel Characterization of Human Body Communication Based on Measured Impulse Response

Joint Sparse Channel Recovery With Quantized Feedback for Multi-User Massive MIMO Systems

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