IEEE journal of radio frequency identification最新文献_第7页

Secure Wireless Information Transfer and Energy Harvesting in HAPS-Based Networks 基于haps网络的安全无线信息传输和能量收集

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-08-28 DOI: 10.1109/JRFID.2026.3728643

Khaled Humadi;Gunes Karabulut-Kurt;Wessam Ajib;Wei-Ping Zhu

{"title":"Secure Wireless Information Transfer and Energy Harvesting in HAPS-Based Networks","authors":"Khaled Humadi;Gunes Karabulut-Kurt;Wessam Ajib;Wei-Ping Zhu","doi":"10.1109/JRFID.2026.3728643","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3728643","url":null,"abstract":"High-altitude platform station (HAPS) serves as a promising enabler for wide-area connectivity of low-power wireless devices, particularly in remote and underserved regions. However, the strong line-of-sight characteristics of HAPS links increase the risk of eavesdropping, while the limited energy budget of ground devices remains a major operational constraint. In this work, we propose a secure wireless information and energy harvesting framework for HAPS-based networks in the presence of spatially distributed eavesdroppers. The proposed system integrates friendly jamming and power transfer nodes equipped with null-steering capability antennas, such that they not only degrade the reception quality at eavesdroppers but also act as additional radio-frequency energy sources for legitimate users. A time-switching wireless information and power transfer architecture is adopted at the user side. Under this framework, we derive tractable expressions for the joint rate-energy coverage and the average secrecy rate using stochastic geometry tools. Numerical and Monte Carlo results validate the developed analysis and reveal key design trade-offs among the time allocation factor, null-steering-zone radius around each user, and jammer transmit power. In particular, the results show that properly coordinated null-steering jamming can simultaneously support secure communication and adequate wireless power transfer, while an appropriate choice of system parameters, such as time allocation factor and jamming power, is required to balance harvested energy, communication reliability, and secrecy performance.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"638-650"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148925441","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}

引用次数: 0

Passive Channelized Cellular IoT System Based on UHF RFID 基于超高频RFID的无源信道蜂窝物联网系统

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-09-02 DOI: 10.1109/JRFID.2026.3730006

Jie Meng;Zihan Huang;Jingfang Su;Zhuohang Zou;Yaolin Yang;Daniele Inserra;Gang Li;Rui Guo;Guangjun Wen

{"title":"Passive Channelized Cellular IoT System Based on UHF RFID","authors":"Jie Meng;Zihan Huang;Jingfang Su;Zhuohang Zou;Yaolin Yang;Daniele Inserra;Gang Li;Rui Guo;Guangjun Wen","doi":"10.1109/JRFID.2026.3730006","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3730006","url":null,"abstract":"To address the challenges of limited coverage range, severe self-interference (SI), and spectrum contraction trends faced by traditional ultra-high frequency radio frequency identification (UHF RFID) technology, a passive channelized cellular IoT system is proposed. A distributed cellular architecture consisting of base stations, helper stations, and tags is established, leveraging in-band frequency division multiplexing (FDM) technology to design a channelized filtering structure for decoupling bidirectional link interference. A temporally-coupled automatic gain control-based self-interference cancellation scheme with a power-compensated joint cancellation structure is developed to counteract fluctuating interference, enhancing adaptability in high-dynamic reflection environments. An in-band segmented linkage frequency hopping (IBSLFH) mechanism based on ping-pong operation is proposed, enabling low-latency dynamic channel switching via channelized frequency hopping (FH) network strategy and extending the system FH range across the entire 5 MHz band. Experimental results demonstrate that the system achieves an effective operating range of 105 m, with a tag recognition rate (TRR) exceeding 90%, at an uplink rate of 160 kbps. Moreover, it attains a TRR of up to 70% in indoor cellular deployments. This provides a practical engineering pathway for long-distance and high-density IoT applications.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"772-784"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985819","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}

引用次数: 0

Is Forecasting Accuracy Enough? A Comparative Study of Traffic Forecasters for Beam-Hopping LEO Satellite Networks 预测准确就足够了吗？波束跳变LEO卫星网络流量预测的比较研究

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-09-07 DOI: 10.1109/JRFID.2026.3731895

Yekta Demirci;Guillaume Mantelet;Stéphane Martel;Jean-François Frigon;Gunes Karabulut Kurt

{"title":"Is Forecasting Accuracy Enough? A Comparative Study of Traffic Forecasters for Beam-Hopping LEO Satellite Networks","authors":"Yekta Demirci;Guillaume Mantelet;Stéphane Martel;Jean-François Frigon;Gunes Karabulut Kurt","doi":"10.1109/JRFID.2026.3731895","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3731895","url":null,"abstract":"We evaluate diverse models for user traffic demand forecasting in Low Earth Orbit (LEO) satellite networks with Beam Hopping (BH), questioning whether predictive accuracy is the right objective for this task. To capture the complex nature of the user traffic demand, we employ a second-order self-similar traffic model, supplemented by a publicly available Wi-Fi dataset to validate the self-similar model against the empirical traffic patterns. We compare forecasters ranging from classical statistical approaches, such as the optimal forecaster for self-similar data and the optimal linear predictor on the discrete sampling grid, to Fractional Auto-Regressive Integrated Moving Average (FARIMA) models, as well as emerging deep learning architectures. The latter category encompasses foundation and domain-specific transformer models, alongside a lightweight neural network consisting solely of linear layers. We assess these models at two levels: in isolation, through the Mean Absolute Scaled Error (MASE), and in context, through a BH simulator in which the forecast drives the illumination plan. On purely self-similar traffic the three self-similarity aware forecasters perform on par with one another and dominate the learned models, whereas on the raw Wi-Fi trace this ordering nearly reverses. Seasonality violates their stationary increment assumption; removing the periodic component restores their comparative accuracy. Crucially, these accuracy differences barely propagate to the system level. Loss ratio and buffer backlog are affected more by system utilization and the planning period than by the choice of forecaster, with the performance gap between forecasters vanishing entirely below 0.90 utilization. This suggests design efforts are better spent optimizing utilization margins and planning periods rather than chasing marginal gains in raw accuracy.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"846-858"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130983","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}

引用次数: 0

Medium Access Control Applied to Long-Range Underwater Acoustic Networks Using an SNR-Aware Adaptive Learning Agent 基于信噪比感知自适应学习代理的远程水声网络介质访问控制

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-09-29 DOI: 10.1109/JRFID.2026.3738523

Yousef Abu Baker;Jean-François Bousquet

{"title":"Medium Access Control Applied to Long-Range Underwater Acoustic Networks Using an SNR-Aware Adaptive Learning Agent","authors":"Yousef Abu Baker;Jean-François Bousquet","doi":"10.1109/JRFID.2026.3738523","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3738523","url":null,"abstract":"In this paper, a signal-to-noise ratio (SNR)-aware deep reinforcement adaptive learning–based medium access control (SNR-DRAL MAC) protocol is proposed for Underwater Acoustic Networks (UANs). By adapting transmission decisions to channel conditions, the proposed approach reduces packet collisions and efficiently utilizes idle time slots left unused by other MAC agents, thereby improving overall network throughput in challenging underwater environments. The novelty of this paper lies in the proposed SNR-aware Deep Reinforcement Adaptive Learning (DRAL) MAC protocol that explicitly couples physical-layer reliability with MAC-layer decision-making under the unique constraints of underwater acoustic networks. By learning directly from the Acknowledgment (ACK) outcomes driven by SNR-dependent Frame Error Rate (FER) and long propagation delays, the proposed agent adapts its transmission policy in a highly non-static channel environment characterized by collisions, burst errors, and delayed feedback. Unlike classical Stop-and-Wait Automatic Repeat reQuest (ARQ)-based ALOHA schemes and prior learning-based MAC approaches such as Actor-Critic, the proposed framework demonstrates robust throughput gains across a wide range of SNR scenarios and under both AWGN and multipath-induced channel variability, thereby validating the effectiveness of learning-based MAC adaptation in realistic underwater environments.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"859-872"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130984","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}

引用次数: 0

Reliability-Margin KBGWO for Robust RFID Network Planning 鲁棒RFID网络规划的可靠性余量KBGWO

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-09-22 DOI: 10.1109/JRFID.2026.3736723

El Miloud Ar-Reyouchi;Saadia Chabel;Hamza Hamout;Abdeljalil Alaoui Douiri;Omar Sefraoui;Kamal Ghoumid

{"title":"Reliability-Margin KBGWO for Robust RFID Network Planning","authors":"El Miloud Ar-Reyouchi;Saadia Chabel;Hamza Hamout;Abdeljalil Alaoui Douiri;Omar Sefraoui;Kamal Ghoumid","doi":"10.1109/JRFID.2026.3736723","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3736723","url":null,"abstract":"This brief paper presents a compact reliability-margin framework for robust radio-frequency identification (RFID) planning in healthcare environments. Deterministic RFID network planning can overestimate indoor healthcare coverage when walls and propagation variability perturb the effective link margin. A reliability-margin Knowledge-Based Grey Wolf Optimizer (KBGWO) is proposed for criticality-aware RFID network planning. Grid readability is estimated from sample-wise Monte Carlo read indicators under stochastic path loss, wall loss, and shadowing. The objective maximizes criticality-weighted reliable coverage and lower-tail reliability while penalizing redundant-read risk, cost, and shortfall from a reliable-coverage target. A small hospital-pilot readability validation compares measured ultra-high-frequency RFID (UHF-RFID) read probabilities with simulated probabilities over line-of-sight (LOS), one-wall, two-wall, metallic-obstructed, and service-core non-line-of-sight (NLOS) locations. The pilot gives mean absolute error (MAE) = 0.029, root mean square error (RMSE) = 0.031, and correlation <inline-formula> <tex-math>$r=0.988$ </tex-math></inline-formula>. Simulations on a hospital-inspired grid show that KBGWO increases reliable coverage from 77.8% to 85.9% and lower-tail reliability from 71.3% to 91.3% versus deterministic KBGWO, at 29% higher cost. Additional checks include external reimplemented baselines, weight sensitivity, Monte Carlo sample stability, ablation, attenuation sensitivity, convergence behavior, perturbed layouts, and raw seed reporting.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"817-821"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130987","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}

引用次数: 0

Scene-Adaptive Modeling and Parameter Prediction for Passive UHF RFID Backscatter Links Under Tag Horizontal Motion 标签水平运动下无源UHF RFID反向散射链路的场景自适应建模与参数预测

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-10-09 DOI: 10.1109/JRFID.2026.3741115

Ruoyu Pan;Yuanlin Liu;Huawei Gou;Jiaqi Liu;Honggang Wang

{"title":"Scene-Adaptive Modeling and Parameter Prediction for Passive UHF RFID Backscatter Links Under Tag Horizontal Motion","authors":"Ruoyu Pan;Yuanlin Liu;Huawei Gou;Jiaqi Liu;Honggang Wang","doi":"10.1109/JRFID.2026.3741115","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3741115","url":null,"abstract":"Mobile passive UHF RFID links exhibit distance-dependent RSSI variations that are influenced by tag velocity, operating frequency, and surrounding structures. To characterize passive UHF RFID links under horizontal tag motion, this paper presents a backscatter-link model that describes motion-related variation separately from environmental propagation effects. A low-speed scan first establishes a quasi-static RSSI reference curve, and a distance sensitivity coefficient and an offset are used to describe the differences between each dynamic measurement and the reference curve. These two parameters are then extracted from measured curves collected under different velocity–frequency conditions. Isotropic radial-basis-function kernel ridge regression (RBF-KRR) is used to model their dependence on tag velocity and operating frequency, and the predicted parameters are used to reconstruct the dynamic RSSI curves. Nested leave-one-condition-out cross-validation is employed for model selection and performance evaluation. In the anechoic-chamber experiments, the proposed model achieves an RSSI root-mean-square error (RMSE) of 0.533 dB, compared with 0.565 dB for linear regression and 0.679 dB for RBF-SVR. In the 920.625-MHz shelf experiments, unadapted chamber-to-shelf transfer yields a pooled held-out RMSE of 2.666 dB. The proposed method retains the motion-related component predicted by the chamber model and uses the shelf measurements to model the remaining propagation error, reducing the RMSE to 0.892 dB. These results demonstrate that modeling motion-related variation separately from environmental propagation error improves RSSI prediction for horizontally moving tags in shelf environments. The proposed model can support RSSI-trend prediction and link-margin evaluation in passive UHF RFID applications involving horizontally moving tags.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"939-952"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11732037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149188206","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}

引用次数: 0

Remote Antenna Impedance Estimation Using a UHF RFID Chip 基于超高频RFID芯片的远程天线阻抗估计

IF 3.4

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-04-27 DOI: 10.1109/JRFID.2026.3687841

Nicolas Barbot;Jesse Tuominen;Antti Paukkunen;Jasmin Grosinger;Pavel Nikitin

引用次数: 0

Transforming RF Reflections Into Respiratory Intelligence Through Radar-ML Synergy 通过雷达- ml协同将射频反射转化为呼吸智能

IF 3.4

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-03-05 DOI: 10.1109/JRFID.2026.3690686

Arnav Hari;Brijesh Kumbhani;Sam Darshi;Satyam Agarwal

{"title":"Transforming RF Reflections Into Respiratory Intelligence Through Radar-ML Synergy","authors":"Arnav Hari;Brijesh Kumbhani;Sam Darshi;Satyam Agarwal","doi":"10.1109/JRFID.2026.3690686","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3690686","url":null,"abstract":"Radar-based contactless monitoring of respiratory rate (RR) plays an important role in a person’s life as it provides a new way of patient observation that does not require physical contact, which medical professionals need for monitoring patients in neonatal intensive care units (NICU) because it safeguards their well-being while maintaining their comfort and stopping the spread of diseases. In this paper, we conduct a comprehensive evaluation of various machine learning (ML) models that use continuous wave (CW) radar data to determine noncontact RR measurements. In a previous paper, we showed that the random forest (RF) algorithm can accurately predict RR but is not up to mark for medical purposes. This study systematically investigates different ML algorithms, which include linear regression (LR), support vector regression (SVR), gradient boosting regression (GBR), XGBoost regression (XGBR), and light gradient boosting machine regression (LGBMR) to evaluate their ability to make predictions and their system performance. These algorithms alone do not provide an accurate prediction of RR monitoring, so we introduce a new hybrid algorithm called stacked ensemble regression (SER), which utilizes an SER framework that integrates various base regressors through a meta-learning method to achieve shared benefits, which allow it to capture both vast linear patterns and small nonlinear changes within respiration data. The proposed SER method achieves an accuracy of 92.24%, which surpasses the performance of XGBR, which achieves an accuracy of 89.65%. The proposed framework creates a strong and expandable system that enables monitoring respiratory patterns through both physical and remote methods while developing radar-based respiratory assessment technology for medical use in hospitals and home care environments.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"391-400"},"PeriodicalIF":3.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147937671","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}

引用次数: 0

Design of a Compact HF and UHF Dual-Band On-Metal RFID Tag Using an Equivalent Circuit Model for Pipeline Marker Applications 基于等效电路模型的紧凑型高频和超高频双频金属RFID标签设计

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-08-25 DOI: 10.1109/JRFID.2026.3727067

Hoyong Kim;Hyunmin Jeong;Donghoon Kim;Seongun Choi;Sangkil Kim

引用次数: 0

Design Strategies for LoRa Backscatter Tags LoRa反向散射标签的设计策略

IF 3.7

IEEE journal of radio frequency identification Pub Date : 2026-01-01 Epub Date: 2026-09-03 DOI: 10.1109/JRFID.2026.3730708

Till Steinmann;Frederik Riedel;Lukas Huth;Tobias Bodewig;Jan Helmerich;Thomas Schaechtle;Stefan J. Rupitsch

{"title":"Design Strategies for LoRa Backscatter Tags","authors":"Till Steinmann;Frederik Riedel;Lukas Huth;Tobias Bodewig;Jan Helmerich;Thomas Schaechtle;Stefan J. Rupitsch","doi":"10.1109/JRFID.2026.3730708","DOIUrl":"https://doi.org/10.1109/JRFID.2026.3730708","url":null,"abstract":"Long Range (LoRa) backscattering has gained increasing popularity, as it enables wireless ultra-low-power long-range communication by reflecting and modulating ambient signals without active Radio Frequency (RF) components. Although operation in the microwatt range is possible, the design of backscatter tags requires balancing synchronization sensitivity, spectral behavior, implementation complexity, and power consumption. This contribution derives design guidelines for LoRa backscatter tags by analyzing two key subsystems: the envelope-detector-based synchronization path and impedance-modulated backscatter transmission. In ambient systems synchronization sensitivity limits the achievable operating range, which is often related to the envelope detector. Therefore, we evaluate low-power amplification strategies, showing that amplifying the demodulated Low-Frequency (LF) signal improves sensitivity by up to 8 dB with only 7 <inline-formula> <tex-math>$mu $ </tex-math></inline-formula>W additional power consumption. Furthermore, amplifier performance is shown to depend on closed-loop bandwidth and LF small-signal behavior rather than gain-bandwidth product alone. In addition, we analyze different impedance-state configurations for backscattering with respect to harmonic suppression, signal strength, implementation complexity, and power consumption. The results reveal that increasing the number of impedance states reduces harmonics but introduces trade-offs between switching complexity and energy consumption. Configurations with up to eight states provide a good balance between spectral performance and implementation effort, while two-state modulation remains preferable for maximizing data rates. Overall, the results presented provide design guidelines for optimizing LoRa backscatter tags in terms of spectral performance, energy efficiency, and communication range, and are also applicable to non-LoRa backscatter communication systems.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":"10 ","pages":"756-771"},"PeriodicalIF":3.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11677094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985813","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}

引用次数: 0