More Web Proxy on the site http://driver.im/

research-article

ILLOC: In-Hall Localization with Standard LoRaWAN Uplink Frames

Authors:

Rui TanAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 6, Issue 1

Article No.: 13, Pages 1 - 26

https://doi.org/10.1145/3517245

Published: 29 March 2022 Publication History

Abstract

LoRaWAN is a narrowband wireless technology for ubiquitous connectivity. For various applications, it is desirable to localize LoRaWAN devices based on their uplink frames that convey application data. This localization service operates in an unobtrusive manner, in that it requires no special software instrumentation to the LoRaWAN devices. This paper investigates the feasibility of unobtrusive localization for LoRaWAN devices in hall-size indoor spaces like warehouses, airport terminals, sports centers, museum halls, etc. We study the TDoA-based approach, which needs to address two challenges of poor timing performance of LoRaWAN narrowband signal and nanosecond-level clock synchronization among anchors. We propose the ILLOC system featuring two LoRaWAN-specific techniques: (1) the cross-correlation among the differential phase sequences received by two anchors to estimate TDoA and (2) the just-in-time synchronization enabled by a specially deployed LoRaWAN end device providing time reference upon detecting a target device's transmission. In a long tunnel corridor, a 70 x 32 m2 sports hall, and a 110 x 70 m2 indoor plaza with extensive non-line-of-sight propagation paths, ILLOC achieves median localization errors of 6 m (with 2 anchors), 8.36 m (with 6 anchors), and 15.16 m (with 6 anchors and frame fusion), respectively. The achieved accuracy makes ILLOC useful for applications including zone-level asset tracking, misplacement detection, airport trolley management, and cybersecurity enforcement like detecting impersonation attacks launched by remote radios.

References

[1]

2020. LimeSDR. https://limemicro.com/products/boards/limesdr/

[2]

2021. HackRF 1MHz to 6GHz SDR Platform. https://www.aliexpress.com/item/32809842995.html.

[3]

2022. gr-lora. https://github.com/rpp0/gr-lora

[4]

Michiel Aernouts, Rafael Berkvens, Koen Van Vlaenderen, and Maarten Weyn. 2018. Sigfox and LoRaWAN datasets for fingerprint localization in large urban and rural areas. Data 3, 2 (2018), 13.

[5]

Roshan Ayyalasomayajula, Aditya Arun, Chenfeng Wu, Sanatan Sharma, Abhishek Rajkumar Sethi, Deepak Vasisht, and Dinesh Bharadia. 2020. Deep learning based wireless localization for indoor navigation. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking. 1--14.

Digital Library

[6]

Roshan Ayyalasomayajula, Deepak Vasisht, and Dinesh Bharadia. 2018. BLoc: CSI-based accurate localization for BLE tags. In Proceedings of the 14th International Conference on emerging Networking EXperiments and Technologies. 126--138.

Digital Library

[7]

Wafae Bakkali, Michel Kieffer, Massinissa Lalam, and Thierry Lestable. 2017. Kalman filter-based localization for Internet of Things LoRaWANTM end points. In 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 1--6.

Digital Library

[8]

Atul Bansal, Akshay Gadre, Vaibhav Singh, Anthony Rowe, Bob Iannucci, and Swarun Kumar. 2021. OwLL: Accurate LoRa Localization using the TV Whitespaces. In Proceedings of the 20th International Conference on Information Processing in Sensor Networks. 148--162.

Digital Library

[9]

Valentina Bianchi, Paolo Ciampolini, and Ilaria De Munari. 2018. RSSI-based indoor localization and identification for ZigBee wireless sensor networks in smart homes. IEEE Transactions on Instrumentation and Measurement 68, 2 (2018), 566--575.

[10]

James Blackman. 2020. Bemis mixes Sigfox and BLE for indoor and outdoor tracking of smart shopping carts. https://enterpriseiotinsights.com/20200622/channels/news/bemis-mixes-sigfox-and-ble-for-indoor-and-outdoor-tracking-of-smart-shopping-carts

[11]

Dongyao Chen, Kang G Shin, Yurong Jiang, and Kyu-Han Kim. 2017. Locating and tracking ble beacons with smartphones. In Proceedings of the 13th International Conference on emerging Networking EXperiments and Technologies. 263--275.

Digital Library

[12]

Pablo Corbalán, Gian Pietro Picco, and Sameera Palipana. 2019. Chorus: UWB concurrent transmissions for GPS-like passive localization of countless targets. In Proceedings of the 18th International Conference on Information Processing in Sensor Networks. IEEE, 133--144.

Digital Library

[13]

Manuel Eichelberger, Kevin Luchsinger, Simon Tanner, and Roger Wattenhofer. 2017. Indoor localization with aircraft signals. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. 1--14.

Digital Library

[14]

Bernat Carbonés Fargas and Martin Nordal Petersen. 2017. GPS-free geolocation using LoRa in low-power WANs. In 2017 Global Internet of Things Summit (Giots). IEEE, 1--6.

[15]

Amalinda Gamage, Jansen Christian Liando, Chaojie Gu, Rui Tan, and Mo Li. 2020. LMAC: Efficient carrier-sense multiple access for lora. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking. 1--13.

Digital Library

[16]

IMST GmbH. 2021. iC880A - LoRa Concentrator. https://shop.imst.de/wireless-modules/lora-products/8/ic880a-spi-lorawan-concentrator-868-mhz.

[17]

Wei Gong and Jiangchuan Liu. 2018. SiFi: Pushing the limit of time-based WiFi localization using a single commodity access point. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 1 (2018), 1--21.

Digital Library

[18]

Bernhard Großwindhager, Michael Stocker, Michael Rath, Carlo Alberto Boano, and Kay Römer. 2019. SnapLoc: An ultra-fast UWB-based indoor localization system for an unlimited number of tags. In Proceedings of the 18th ACM/IEEE International Conference on Information Processing in Sensor Networks. 61--72.

Digital Library

[19]

Chaojie Gu, Linshan Jiang, Rui Tan, Mo Li, and Jun Huang. 2021. Attack-aware synchronization-free data timestamping in lorawan. ACM Transactions on Sensor Networks (TOSN) 18, 1 (2021), 1--31.

Digital Library

[20]

Zhe He, You Li, Ling Pei, and Kyle O'Keefe. 2018. Enhanced Gaussian process-based localization using a low power wide area network. IEEE Communications Letters 23, 1 (2018), 164--167.

[21]

Bashima Islam, Md Tamzeed Islam, Jasleen Kaur, and Shahriar Nirjon. 2019. Lorain: Making a case for lora in indoor localization. In 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, 423--426.

[22]

Chengkun Jiang, Yuan He, Songzhen Yang, Junchen Guo, and Yunhao Liu. 2019. 3D-OmniTrack: 3D tracking with COTS RFID systems. In Proceedings of the 18th ACM/IEEE International Conference on Information Processing in Sensor Networks. 25--36.

Digital Library

[23]

Damien B Jourdan and Nicholas Roy. 2008. Optimal sensor placement for agent localization. ACM Transactions on Sensor Networks (TOSN) 4, 3 (2008), 1--40.

Digital Library

[24]

Nicolaj Kirchhof. 2013. Optimal placement of multiple sensors for localization applications. In International Conference on Indoor Positioning and Indoor Navigation. IEEE, 1--10.

[25]

Manikanta Kotaru, Kiran Joshi, Dinesh Bharadia, and Sachin Katti. 2015. Spotfi: Decimeter level localization using wifi. In Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication. 269--282.

Digital Library

[26]

Swarun Kumar, Stephanie Gil, Dina Katabi, and Daniela Rus. 2014. Accurate indoor localization with zero start-up cost. In Proceedings of the 20th annual international conference on Mobile computing and networking. 483--494.

Digital Library

[27]

Swarun Kumar, Ezzeldin Hamed, Dina Katabi, and Li Erran Li. 2014. LTE radio analytics made easy and accessible. ACM SIGCOMM Computer Communication Review 44, 4 (2014), 211--222.

Digital Library

[28]

Ye-Sheng Kuo, Pat Pannuto, Ko-Jen Hsiao, and Prabal Dutta. 2014. Luxapose: Indoor positioning with mobile phones and visible light. In Proceedings of the 20th annual international conference on Mobile computing and networking. 447--458.

Digital Library

[29]

Myeongcheol Kwak, Youngmong Park, Junyoung Kim, Jinyoung Han, and Taekyoung Kwon. 2018. An energy-efficient and lightweight indoor localization system for Internet-of-Things (IoT) environments. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 1 (2018), 1--28.

Digital Library

[30]

Hussein Kwasme and Sabit Ekin. 2019. RSSI-based localization using LoRaWAN technology. IEEE Access 7 (2019), 99856--99866.

[31]

Ka-Ho Lam, Chi-Chung Cheung, and Wah-Ching Lee. 2019. RSSI-Based LoRa Localization Systems for Large-Scale Indoor and Outdoor Environments. IEEE Transactions on Vehicular Technology 68, 12 (2019), 11778--11791.

[32]

Richard B Langley et al. 1999. Dilution of precision. GPS world 10, 5 (1999), 52--59.

[33]

Patrick Lazik, Niranjini Rajagopal, Oliver Shih, Bruno Sinopoli, and Anthony Rowe. 2015. ALPS: A bluetooth and ultrasound platform for mapping and localization. In Proceedings of the 13th ACM conference on Embedded Networked Sensor Systems. 73--84.

Digital Library

[34]

Liqun Li, Pan Hu, Chunyi Peng, Guobin Shen, and Feng Zhao. 2014. Epsilon: a visible light based positioning system. In Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation. 331--343.

[35]

Yuxiang Lin, Wei Dong, Yi Gao, and Tao Gu. 2020. SateLoc: A Virtual Fingerprinting Approach to Outdoor LoRa Localization using Satellite Images. In Proceedings of the 19th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[36]

Jun Liu, Jiayao Gao, Sanjay Jha, and Wen Hu. 2021. Seirios: leveraging multiple channels for LoRaWAN indoor and outdoor localization. In Proceedings of the 27th Annual International Conference on Mobile Computing and Networking. 656--669.

Digital Library

[37]

Inc. LoRa Alliance. 2017. LoRaWAN 1.1 Specification.

[38]

Yunfei Ma, Nicholas Selby, and Fadel Adib. 2017. Minding the billions: Ultra-wideband localization for deployed rfid tags. In Proceedings of the 23rd annual international conference on mobile computing and networking. 248--260.

Digital Library

[39]

Sandeep Mistry. 2022. Arduino-LoRa. https://github.com/sandeepmistry/arduino-LoRa

[40]

Ruthwik Muppala, Abhinav Navnit, Deeksha Devendra, Eustachio Roberto Matera, Nicola Accettura, and Aftab M Hussain. 2021. Feasibility of Standalone TDoA-based Localization Using LoRaWAN. In International Conference on Localization and GNSS. IEEE, 1--7.

[41]

Rajalakshmi Nandakumar, Vikram Iyer, and Shyamnath Gollakota. 2018. 3d localization for sub-centimeter sized devices. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. 108--119.

Digital Library

[42]

Ryosuke Okuta, Yuya Unno, Daisuke Nishino, Shohei Hido, and Crissman Loomis. 2017. CuPy: A NumPy-Compatible Library for NVIDIA GPU Calculations. In NIPS Workshop. http://learningsys.org/nips17/assets/papers/paper_16.pdf

[43]

Veljo Otsason, Alex Varshavsky, Anthony LaMarca, and Eyal De Lara. 2005. Accurate GSM indoor localization. In International conference on ubiquitous computing. Springer, 141--158.

Digital Library

[44]

Messaoud Ahmed Ouameur, Manouane Caza-Szoka, and Daniel Massicotte. 2020. Machine learning enabled tools and methods for indoor localization using low power wireless network. Internet of Things (2020), 100300.

[45]

Nico Podevijn, David Plets, Jens Trogh, Luc Martens, Pieter Suanet, Kim Hendrikse, and Wout Joseph. 2018. TDoA-based outdoor positioning with tracking algorithm in a public LoRa network. Wireless Communications and Mobile Computing (2018).

[46]

Jait Purohit, Xuyu Wang, Shiwen Mao, Xiaoyan Sun, and Chao Yang. 2020. Fingerprinting-based indoor and outdoor localization with LoRa and deep learning. In IEEE Global Communications Conference. IEEE, 1--6.

Digital Library

[47]

Niranjini Rajagopal, Sindhura Chayapathy, Bruno Sinopoli, and Anthony Rowe. 2016. Beacon placement for range-based indoor localization. In 2016 international conference on indoor positioning and indoor navigation (IPIN). IEEE, 1--8.

[48]

Hamada Rizk, Marwan Torki, and Moustafa Youssef. 2018. CellinDeep: Robust and accurate cellular-based indoor localization via deep learning. IEEE Sensors Journal 19, 6 (2018), 2305--2312.

[49]

Hazem Sallouha, Alessandro Chiumento, and Sofie Pollin. 2017. Localization in long-range ultra narrow band IoT networks using RSSI. In 2017 IEEE International Conference on Communications (ICC). IEEE, 1--6.

[50]

Semtech. 2021. Locating End Devices with Semtech's LoRa CloudTM Geolocation Service. https://lora-developers.semtech.com/documentation/tech-papers-and-guides/locating-end-devices-with-lora-cloud/

[51]

Semtech. 2021. Semtech and DevAppSol Track Luggage Trolleys to Reduce Airport Management Cost With LoRaWAN. https://www.semtech.com/company/press/semtechs-and-devappsol-track-luggage-trolleys-to-reduce-airport-management-cost-with-lorawan

[52]

Masashi Sugano, Tomonori Kawazoe, Yoshikazu Ohta, and Masayuki Murata. 2006. Indoor Localization System using RSSI Measurement of Wireless Sensor Network based on ZigBee Standard. Wireless and Optical Communications (2006), 1--6.

[53]

Vamsi Talla, Mehrdad Hessar, Bryce Kellogg, Ali Najafi, Joshua R Smith, and Shyamnath Gollakota. 2017. Lora backscatter: Enabling the vision of ubiquitous connectivity. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 1--24.

Digital Library

[54]

Rui Tian, HaiBo Ye, and Li Sheng. 2020. Indoor Localization Based on the LoRa Technology. In International Conference on Machine Learning and Intelligent Communications. Springer, 304--319.

[55]

Xinyu Tong, Fengyuan Zhu, Yang Wan, Xiaohua Tian, and Xinbing Wang. 2019. Batch localization based on OFDMA backscatter. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 1 (2019), 1--25.

Digital Library

[56]

Junpei Tsuji, Hidenori Kawamura, Keiji Suzuki, Takeshi Ikeda, Akio Sashima, and Koichi Kurumatani. 2010. ZigBee based indoor localization with particle filter estimation. In 2010 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 1115--1120.

[57]

Deepak Vasisht, Guo Zhang, Omid Abari, Hsiao-Ming Lu, Jacob Flanz, and Dina Katabi. 2018. In-body backscatter communication and localization. In Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication. 132--146.

Digital Library

[58]

Davide Vecchia, Pablo Corbalán, Timofei Istomin, and Gian Pietro Picco. 2019. TALLA: Large-scale TDoA localization with ultra-wideband radios. In 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 1--8.

[59]

Jue Wang, Fadel Adib, Ross Knepper, Dina Katabi, and Daniela Rus. 2013. RF-compass: Robot object manipulation using RFIDs. In Proceedings of the 19th annual International Conference on Mobile Computing and Networking. 3--14.

Digital Library

[60]

Jue Wang and Dina Katabi. 2013. Dude, where's my card? RFID positioning that works with multipath and non-line of sight. In Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM. 51--62.

Digital Library

[61]

Jiang Xiao, Zimu Zhou, Youwen Yi, and Lionel M Ni. 2016. A survey on wireless indoor localization from the device perspective. ACM Computing Surveys (CSUR) 49, 2 (2016), 1--31.

Digital Library

[62]

Bo Xie, Guang Tan, and Tian He. 2015. Spinlight: A high accuracy and robust light positioning system for indoor applications. In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems. 211--223.

Digital Library

[63]

Pengjin Xie, Lingkun Li, Jiliang Wang, and Yunhao Liu. 2020. LiTag: localization and posture estimation with passive visible light tags. In Proceedings of the 18th Conference on Embedded Networked Sensor Systems. 123--135.

Digital Library

[64]

Jie Xiong, Karthikeyan Sundaresan, and Kyle Jamieson. 2015. Tonetrack: Leveraging frequency-agile radios for time-based indoor wireless localization. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. 537--549.

Digital Library

[65]

Huatao Xu, Dong Wang, Run Zhao, and Qian Zhang. 2019. AdaRF: Adaptive RFID-based indoor localization using deep learning enhanced holography. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 3 (2019), 1--22.

Digital Library

[66]

Xuehan Ye, Shuo Huang, Yongcai Wang, Wenping Chen, and Deying Li. 2019. Unsupervised localization by learning transition model. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 2 (2019), 1--23.

Digital Library

[67]

Faheem Zafari, Athanasios Gkelias, and Kin K Leung. 2019. A survey of indoor localization systems and technologies. IEEE Communications Surveys & Tutorials 21, 3 (2019), 2568--2599.

[68]

Chi Zhang and Xinyu Zhang. 2017. Pulsar: Towards ubiquitous visible light localization. In Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking. 208--221.

Digital Library

[69]

Fusang Zhang, Zhaoxin Chang, Kai Niu, Jie Xiong, Beihong Jin, Qin Lv, and Daqing Zhang. 2020. Exploring lora for long-range through-wall sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 2 (2020), 1--27.

Digital Library

[70]

Fusang Zhang, Zhaoxin Chang, Jie Xiong, Rong Zheng, Junqi Ma, Kai Niu, Beihong Jin, and Daqing Zhang. 2021. Unlocking the beamforming potential of lora for long-range multi-target respiration sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, 2 (2021), 1--25.

Digital Library

[71]

Hongxu Zhu, Kim-Fung Tsang, Yucheng Liu, Yang Wei, Hao Wang, Chung Kit Wu, and Hao Ran Chi. 2020. Extreme RSS based Indoor Localization for LoRaWAN with Boundary Autocorrelation. IEEE Transactions on Industrial Informatics 17, 7 (2020), 4458--4468.

Cited By

Kim DSuh Y(2024)Automatic Fingerprint Data Labeling Using WiFi Signal and Smartphone Camera for Indoor PositioningWireless Communications & Mobile Computing10.1155/2024/86632462024Online publication date: 10-Jun-2024
https://dl.acm.org/doi/10.1155/2024/8663246
Yang KChen YDu WOkoshi TKo JLiKamWa R(2024)OrchLoc: In-Orchard Localization via a Single LoRa Gateway and Generative Diffusion Model-based FingerprintingProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661876(304-317)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661876
Zhang TZhang DWang GLi YHu Ysun QChen Y(2024)RLocProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314377:4(1-28)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631437
Show More Cited By

Index Terms

ILLOC: In-Hall Localization with Standard LoRaWAN Uplink Frames
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Sensor networks
2. Networks
  1. Network components
    1. Wireless access points, base stations and infrastructure
  2. Network services
    1. Location based services

Recommendations

Bringing UWB Indoor Localization Closer to being Universal and Pervasive
UbiComp/ISWC '22 Adjunct: Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers

Location-based services have the potentials to change how we interact with the places and things around us. UWB indoor localization is one of the most successful enabling technologies that has achieved decimeter accuracy with robustness against complex ...
A Polygonal Method for Ranging-Based Localization in an Indoor Wireless Sensor Network

In this paper, we propose an indoor localization method in a wireless sensor network based on IEEE 802.15.4 specification. The proposed method follows a ranging-based approach using not only the measurements of received signal strength (RSS) but also ...
SALMA: UWB-based Single-Anchor Localization System using Multipath Assistance
SenSys '18: Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems

Setting up indoor localization systems is often excessively time-consuming and labor-intensive, because of the high amount of anchors to be carefully deployed or the burdensome collection of fingerprints. In this paper, we present SALMA, a novel low-...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 6, Issue 1

March 2022

1009 pages

EISSN:2474-9567

DOI:10.1145/3529514

Issue’s Table of Contents

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2022

Published in IMWUT Volume 6, Issue 1

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

Joint NTU-WeBank Research Centre on FinTech

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

17
Total Citations
View Citations
437
Total Downloads

Downloads (Last 12 months)121
Downloads (Last 6 weeks)6

Reflects downloads up to 17 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Kim DSuh Y(2024)Automatic Fingerprint Data Labeling Using WiFi Signal and Smartphone Camera for Indoor PositioningWireless Communications & Mobile Computing10.1155/2024/86632462024Online publication date: 10-Jun-2024
https://dl.acm.org/doi/10.1155/2024/8663246
Yang KChen YDu WOkoshi TKo JLiKamWa R(2024)OrchLoc: In-Orchard Localization via a Single LoRa Gateway and Generative Diffusion Model-based FingerprintingProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661876(304-317)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661876
Zhang TZhang DWang GLi YHu Ysun QChen Y(2024)RLocProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314377:4(1-28)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631437
Guo XHe YZhang JLiu YShangguan L(2024)Towards Programmable Backscatter Radio Design for Heterogeneous Wireless NetworksIEEE/ACM Transactions on Networking10.1109/TNET.2024.345409532:6(5020-5032)Online publication date: Dec-2024
https://doi.org/10.1109/TNET.2024.3454095
Liu BGu CHe SChen J(2024)LoPhy: A Resilient and Fast Covert Channel Over LoRa PHYIEEE/ACM Transactions on Networking10.1109/TNET.2024.339881432:5(3792-3807)Online publication date: Oct-2024
https://doi.org/10.1109/TNET.2024.3398814
Guo XHe YNan JZhang JLiu YShangguan L(2024)A Low-Power Demodulator for LoRa Backscatter Systems With Frequency-Amplitude TransformationIEEE/ACM Transactions on Networking10.1109/TNET.2024.339650932:4(3515-3527)Online publication date: Aug-2024
https://doi.org/10.1109/TNET.2024.3396509
Hou NXia XWang YZheng Y(2024)One Shot for All: Quick and Accurate Data Aggregation for LPWANsIEEE/ACM Transactions on Networking10.1109/TNET.2024.335379232:3(2285-2298)Online publication date: Jun-2024
https://doi.org/10.1109/TNET.2024.3353792
Matsunaga TArai IAtarashi YEndo AFujikawa K(2024)Performance Evaluation of Fingerprint-Based Indoor Positioning Using RSSI in 802.11ah2024 14th International Conference on Indoor Positioning and Indoor Navigation (IPIN)10.1109/IPIN62893.2024.10786180(1-7)Online publication date: 14-Oct-2024
https://doi.org/10.1109/IPIN62893.2024.10786180
Li YWang SXu SYin J(2024)Trustworthy semi‐supervised anomaly detection for online‐to‐offline logistics business in merchant identificationCAAI Transactions on Intelligence Technology10.1049/cit2.123019:3(544-556)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1049/cit2.12301
Lutakamale AMyburgh Hde Freitas A(2024)A hybrid convolutional neural network-transformer method for received signal strength indicator fingerprinting localization in Long Range Wide Area NetworkEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108349133:PDOnline publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1016/j.engappai.2024.108349
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents