• Communication Technology
    • Communication Modality: Wi-Fi / BLE / Acoustic / Vision / Light / UWB / Infrared / EMF / mmWave / Multiple
    • Localization Methods: Model-based / Fingerprinting
    • Research Focus: Localization Algoirtihm / Anchor / Evaluation
    • Scale: Small (Room Level) / Large (Building Level) / Ubiquitous (Multiple Building or City Level)
    • Target Type: Device-based / Device-free
    • Granularity: Room Level / Meters / Decimeters / Centimeter


  • Many VLP (Visible Light Positioning) conducts modification on the light fixture, hence can be viewed as frontier works on anchorlization.

Special Topics

  • Localization over Large-Scale 802.11, MobiCom 04, haeberlen2004practical
    • Taxonomy: Wi-Fi, Fingerprinting, Localization Methods, Large (Building Level), Room Level
    • Pros: Less time in fingerprinting;
  • Metropolitan-scale Wi-Fi Localization, MobiSys 05, cheng2005accuracy
    • Taxonomy: Wi-Fi, Evaluation, Ubiquitous,
    • Pros: Metropolitan-scale coverage
    • Cons: Lower accuracy
  • EZ: Indoor Localization without Pain, MobiCom 10, chintalapudi2010indoor
    • Taxonomy: Wi-Fi, Localization Algorithm,
    • Pros: No need for physical layout, i.e. the position of AP is unknown; No need for calibration
    • Cons: Dense deployment of AP
    • Assumptions: universal LDPL equation (as constraints), occasional location fix (entrance, window)
  • Adaptive GPS Duty Cycling and Radio Ranging, SenSys10
    • This is not a indoor localization paper, but provide a very good description on the relation between RSSI and distance as shown in the following

RSSI Features

  • LiFS: Locating in Fingerprint Space, MobiCom 12, yang2012locating
    • Taxonomy: Wi-Fi, Fingerprinting, Localization Algoirtihm, Large-Scale,
    • Pros: Reduced fingerprinting workload, Large scale;
  • Zee: Zero-Effort Crowdsourcing, MobiCom 12, rai2012zee
    • Taxonomy: Wi-Fi, Fingerprinting, Localization Algorithm, Large Scale
    • Pros: No need for site-specific calibration, No assumption on phone position
    • Assumptions: Map available showing pathways and barriers
  • UnLoc: Unsupervised Indoor Localization, MobiSys 12, wang2012no
    • Taxonomy: Multiple, Anchor, Meters Level,
    • Signal landmarks in the building as anchors
    • Dead reckoning using to locate between anchors
    • Cons: Device diversity not considered, Landmark not available everywhere
  • Guoguo: Acoustic Fingraind Indoor Localization, MobiSys 13, liu2013guoguo
    • Taxonomy: Acoustic, Model-based, Localization Algorithm + Anchor, Small Scale
  • Social-Loc: Improving Indoor Localization with Social Sensing, SenSys 13, jun2013social
    • Taxonomy: Multiple, Localization Algoirtihm, Small-Scale
  • Ubicarse: Indoor Localization With Zero Start-up Cost, MobiCom 14, kumar2014accurate
    • Taxonomy: Wi-Fi+Carmera, Model-based, Localization Algorithm,
    • Assume AP location is known
  • Modellet: Diversity in Data Density and Environmental Locality, MobiCom 14, li2014experiencing
    • Taxonomy: Fingerprinting, Localization Algorithm, Ubiquitous,
    • Pros: Can handle diversity in training data density and environment condition for real-world deployment
    • Cons: Device diversity is not considered; still relies on fingerprint. (which is impossible in real large scale problem)
  • Jigsaw: Indoor Floor Plan Reconstruction, MobiCom 14, gao2014jigsaw
    • Taxonomy: Vision, Anchor, Large Scale
    • Cons: Need input images
  • Luxapose: Indoor Positioning with Visible Light, MobiCom 14, kuo2014luxapose
    • Taxonomy: Light, Model-based, Localization Algorithm+Anchor, Decimeter, Small-Scale
    • Cons: Need image capture periodically
  • SAIL: Single Access Point-Based Indoor Localization, MobiSys 14, mariakakis2014sail
    • Taxonomy: Wi-Fi, Localization Algorithm, Model-based, Large-Scale, Meters Level,
    • Pros: Only need single AP,
  • EchoTag: Indoor Location Tagging with Smartphones, MobiCom 15, tung2015echotag
    • Taxonomy: Acoustic, Localization Algorithm + Anchor,
  • ToneTrack: Frequency-Agile Radios for Indoor Localization, MobiCom 15, xiong2015tonetrack
    • Taxonomy: Wi-Fi, Localization Algorithm, Small-scale
  • PIXEL: Light-weight Indoor Positioning with Visible Light, MobiSys 15, yang2015wearables
    • Taxonomy: Light, Localization Algorithm, Small Scale
    • Pros: Light-weight that can run on resource-constrianed platforms
  • INTRI: Contour-based Trilateration for Indoor Fingerprinting Localization, SenSys 15, he2015contour
    • Taxonomy: Wi-Fi, Localization Algorithm, Large-Scale
  • SpinLight: High Accuracy and Robust Light Positioning System, SenSys 15, xie2015spinlight
    • Taxonomy: Light, Localization Algorithm + Anchor, Small Scale, Centimeter
    • Pros: 2D+3D localization
    • Cons: Light sensor needed
  • Towards Truly Ubiquitous Indoor Localization on a Worldwide Scale, SIGSPATIAL 15, youssef2015towards
    • Taxonomy: Ubiquitous,
    • Pros and Cons: Challenges and only challenges.
  • LiFS: Low Human-Effort, Device-Free Localization, MobiCom 16, wang2016lifs
    • Taxonomy: Wi-Fi, Model-based, Small-Scale
    • Pros: No offline training
    • Cons: Known AP location
  • LiTell: Robust Indoor Localization Using Unmodified Light Fixtures, MobiCom 16, zhang2016litell
    • Taxonomy: Light, Large-Scale, Localization Algorithm, Fingerprinting
    • Pros: No hardware modifications;
  • NAVIQ: In-door WiFi-Beacon Navigation System Without Exact Location, MobiSys 16
    • Taxonomy: Navigation, BLE,
  • Pulsar: Ubiquitous Visible Light Localization, MobiCom 17, zhang2017pulsar
    • Taxonomy: Light, Localization Methods, (claimed to be) Ubiquitous
    • Pros: No modification on light fixtures
  • CELLI: Indoor Positioning Using Polarized Sweeping Light Beams, MobiSys 17, wei2017celli
    • Taxonomy: Light, Centimeter, Anchor+Localization Algorithm
    • Pros: Only needs one transmitter and one sensor
  • iLAMP: High-Precision Visible Light Localization, MobiSys 17, zhu2017enabling
    • Taxonomy: Light, Large-Scale, Localization Algorithm
  • SmartLight: 3D Indoor Localization Using a Single LED Lamp, SenSys 17, liu2017smartlight
    • Taxonomy: Light, Small-Scale, Decimeter
    • Pros: Locates large number of sensors
    • Cons: LED light modification needed
  • RainbowLight: Low Cost Ambient Light Positioning System, MobiCom 18, li2018rainbowlight
    • Taxonomy: Light, Localization Algorithm,
  • EMF: Localization and Mapping with Power Network Electromagnetic Field, MobiCom 18, lu2018simultaneous
    • Taxonomy: EMF, Anchor+Localization Algorithm
  • ZhaoTian: Augmenting Indoor Inertial Tracking with Polarized Light, MobiSys 18, tian2018augmenting
    • Taxonomy: Light+IMU, Anchor+Localization Algorithm
  • MonoLoco: Multipath Triangulation: WiFi Localization and Orientation, MobiSys 18, soltanaghaei2018multipath
    • Taxonomy: Wi-Fi, Localization Algorithm, Decimeter-level, Small Scale
    • Pros: Only need single AP
  • Widar2.0: Passive Human Tracking with a Single Wi-Fi Link, MobiSys 18, qian2018widar2
    • Taxonomy: Wi-Fi, Localization Algorithm
    • Pros: Only need one single Wi-Fi link
  • mWaveLoc: Accurate 3D Localization for 60 GHz Networks, SenSys 18
    • Taxonomy: mmWave, Centimeter-level,
    • Pros: High accuracy
  • Toward Reliable Localization by Unequal AoA Tracking, MobiSys19
    • Taxonomy: Wi-Fi, AoA


[MobiCom04] Andreas Haeberlen, Eliot Flannery, Andrew M. Ladd, Algis Rudys, Dan S. Wallach, and Lydia E. Kavraki. 2004. Practical Robust Localization over Large-Scale 802.11 Wireless Networks Andreas. In ACM MobiCom, 60–61.

[MobiSys05] Yu-Chung Cheng, Yatin Chawathe, Anthony LaMarca, and John Krumm. 2005. Accuracy characterization for metropolitan-scale Wi-Fi localization. In ACM MobiSys, 233.

[MobiCom10-EZ] Krishna Chintalapudi. 2010. Indoor Localization Without the Pain. In ACM MobiCom, 173–184.

[SenSys10-Adaptive] Jurdak, R., Corke, P., Dharman, D., & Salagnac, G. (2010, November). Adaptive GPS duty cycling and radio ranging for energy-efficient localization. In SenSys (pp. 57-70). ACM.

[MobiCom12-LiFS] Zheng Yang, Chenshu Wu, and Yunhao Liu. 2012. Locating in Fingerprint Space : Wireless Indoor Localization with Little Human Intervention. In ACM MobiCom, 269–280.

[MobiCom12-Zee] Anshul Rai. 2012. Zee : Zero-Effort Crowdsourcing for Indoor Localization Categories and Subject Descriptors. In ACM MobiCom, 293–304.

[MobiSys12-UnLoc] He Wang, S Sen, and Ahmed Elgohary. 2012. No need to war-drive: Unsupervised indoor localization. ACM MobiSys, 197–210.

[MobiSys13-Guoguo] Kaikai Liu, Xinxin Liu, and Xiaolin Li. 2013. Guoguo: Enabling Fine-grained Indoor Localization via Smartphone. ACM MobiSys, 235.

[MobiCom14-Modellet] Li, L., 2014, Experiencing and handling the diversity in data density and environmental locality in an indoor positioning service. In ACM MobiCom 59-470

[MobiCom14-Ubicarse] Swarun Kumar, Stephanie Gil, Dina Katabi, and Daniela Rus. 2014. Accurate Indoor Localization With Zero Start-up Cost. In ACM MobiCom, 483–494.

[MobiCom14-Jigsaw] Ruipeng Gao, Mingmin Zhao, Tao Ye, Fan Ye, Yizhou Wang, Kaigui Bian, Tao Wang, and Xiaoming Li. 2014. Jigsaw : Indoor Floor Plan Reconstruction via Mobile Crowdsensing. In ACM MobiCom, 249–260.

[MobiCom14-Luxapose] Ye-Sheng Kuo, Pat Pannuto, Ko-Jen Hsiao, and Prabal Dutta. 2014. Luxapose: Indoor Positioning with Mobile Phones and Visible Light. In ACM MobiCom, 447–458.

[SenSys15-INTRI:] Suining He, Tianyang Hu, and S.-H Gary Chan. 2015. Contour-based Trilateration for Indoor Fingerprinting Localization. In ACM SenSys.

[SIGCOMM15-SpotFi] Manikanta Kotaru, Kiran Joshi, Dinesh Bharadia, and Sachin Katti. 2015. SpotFi: Decimeter Level Localization Using WiFi. In ACM SIGCOMM, 269–282.

[SIGSPATIAL15] Youssef, M. (2015, November). Towards truly ubiquitous indoor localization on a worldwide scale. In Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems (p. 12). ACM.

[MobiCom16-LiFS] Ju Wang, Hongbo Jiang, Jie Xiong, Kyle Jamieson, Xiaojiang Chen, Dingyi Fang, and Binbin Xie. 2016. LiFS: Low Human-Effort, Device-Free Localization with Fine-Grained Subcarrier Information. In ACM MobiCom, 243–256.

[MobiCom16-LiTell] Chi Zhang and Xinyu Zhang. 2016. LiTell: indoor localization using unmodified light fixtures. In ACM MobiCom, 481–482.

[MobiSys16-NAVIQ] Huang, Q. 2016,. Poster: Simplified In-door WiFi-Beacon Navigation System Without Exact Location. In ACM MobiSys 33-33

[MobiCom17-Pulsar] Chi Zhang and Xinyu Zhang. 2017. Pulsar: Towards Ubiquitous Visible Light Localization. In ACM MobiCom, 208–221.

[MobiSys17-CELLI] Yu-Lin Wei, Chang-Jung Huang, Hsin-Mu Tsai, and Kate Ching-Ju Lin. 2017. CELLI: Indoor Positioning Using Polarized Sweeping Light Beams. In ACM MobiSys, 136–147.

[MobiSys17-iLAMP] Shilin Zhu and Xinyu Zhang. 2017. Enabling High-Precision Visible Light Localization in Today’s Buildings. In ACM MobiSys, 96–108.

[SenSys17-SmartLight] Song Liu and Tian He. 2017. SmartLight: Light-weight 3D Indoor Localization Using a Single LED Lamp. In ACM SenSys, 11:1–11:14.

[MobiCom18-RainbowLight] Lingkun Li, Pengjin Xie, and Jiliang Wang. 2018. Demo : RainbowLight : Design and Implementation of a Low Cost Ambient Light Positioning System. In ACM MobiCom, 807–809.

[MobiCom18-EMF] Chris Xiaoxuan Lu, Yang Li, Peijun Zhao, Changhao Chen, Linhai Xie, Hongkai Wen, Rui Tan, and Niki Trigoni. 2018. Simultaneous Localization and Mapping with Power Network Electromagnetic Field. In ACM MobiCom, 607–622.

[SenSys18-Salma] Bernhard Großwindhager, Michael Rath, Josef Kulmer, Mustafa S. Bakr, Carlo Alberto Boano, Klaus Witrisal, and Kay Römer. 2018. Salma: UWB-based single-Anchor Localization System using Multipath Assistance. ACM SenSys October (2018), 132–144.

[MobiSys18-ZhaoTian] Zhao Tian, Yu-Lin Wei, Wei-Nin Chang, Xi Xiong, Changxi Zheng, Hsin-Mu Tsai, Kate Ching-Ju Lin, and Xia Zhou. 2018. Augmenting Indoor Inertial Tracking with Polarized Light. In ACM MobiSys.

[MobiSys18-MonoLoco] Elahe Soltanaghaei, Avinash Kalyanaraman, and Kamin Whitehouse. 2018. Multipath Triangulation: Decimeter-level WiFi Localization and Orientation with a Single Unaided Receiver. In ACM MobiSys

[MobiSys18-Widar2.0] Kun Qian, Chenshu Wu, Yi Zhang, Guidong Zhang, Zheng Yang, Yunhao Liu, and Yun-Hao Liu. 2018. Widar2.0: Passive Human Tracking with a Single Wi-Fi Link. In ACM MobiSys, 12.

[SenSys18-mWaveLoc] Ioannis Pefkianakis and Kyu-Han Kim. 2018. Accurate 3D Localization for 60 GHz Networks. In ACM SenSys, 120–131.

[MobiSys19]Tai, T. C., Lin, K. C. J., & Tseng, Y. C. (2019, June). Toward Reliable Localization by Unequal AoA Tracking. In MobiSys (pp. 444-456). ACM.