Network-side positioning of cellular-band devices with minimal effort

Proceedings - IEEE INFOCOM

Volumn 26, Issue , 2015, Pages 2767-2775

  Chakraborty, Ayon ^a   Ortiz, Luis E ^a   Das, Samir R ^a  

^a Stony Brook University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

CELLULAR OPERATORS; CONFIDENCE MEASURE; ERROR CHARACTERISTICS; IMPROVE PERFORMANCE; LOCALIZATION ACCURACY; SIGNAL STRENGTH MEASUREMENTS; SPATIAL PROPERTIES; UNSUPERVISED MACHINE LEARNING;

LEARNING SYSTEMS;

EID: 84954226260     PISSN: 0743166X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INFOCOM.2015.7218669     Document Type: Conference Paper

References (28)

1. Wireless EM propagation software. http: //www. remcom. com/ wireless-insite.
2. A. Achtzehn, J. Riihijarvi, and P. Mahonen. Improving accuracy for TVWS geolocation databases: Results from measurement-driven estimation approaches. In Proceedings IEEE DySPAN, 2014.
3. M. Y. Chen et al. Practical metropolitan-scale positioning for GSM phones. In Proceedings of ACM UbiComp, 2006.
4. K. Chintalapudi, A. Padmanabha Iyer, and V. N. Padmanabhan. Indoor localization without the pain. In Proceedings of ACM MobiCom, 2010.
5. A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B, 39: 1-38, 1977.
6. P. Domingos and M. Pazzani. On the optimality of the simple bayesian classifier under zero-one loss. Machine Learning, 29(2-3): 103-130, 1997.
7. A. Goswami, L. E. Ortiz, and S. R. Das. WiGEM: A learning-based approach for indoor localization. In Proceedings of ACM CoNEXT, 2011.
8. B. Hahnel, F. Dirk, and D. Fox. Gaussian processes for signal strengthbased location estimation. In Proceeding of Robotics: Science and Systems, 2006.
9. M. Ibrahim and M. Youssef. A hidden markov model for localization using low-end gsm cell phones. In Proceedings of IEEE ICC, 2011.
10. M. Ibrahim and M. Youssef. Cellsense: An accurate energy-efficient gsm positioning system. Vehicular Technology, IEEE Transactions on, 61(1): 286-296, 2012.
11. M. Ibrahim and M. Youssef. Enabling wide deployment of GSM localization over heterogeneous phones. In Proceeding of ICC, 2013.
12. H. Lim et al. Zero-configuration, robust indoor localization: Theory and experimentation. In Proceedings of IEEE Infocom, 2006.
13. E. Martin et al. Precise indoor localization using smart phones. In Proceedings of ACM Multimedia, 2010.
14. P. A. P. Moran. Notes on continuous stochastic phenomena. Biometrika, 37: 1733, 1950.
15. K. P. Murphy. Machine Learning: A Probabilistic Perspective. The MIT Press, Cambridge, MA, 2012.
16. P. Nurmi, S. Bhattacharya, and J. Kukkonen. A grid-based algorithm for on-device gsm positioning. In Proceedings of ACM UbiComp, 2010.
17. M. Rahnema. UMTS network planning, optimization, and interoperation with GSM. Wiley-IEEE Press, 2008.
18. A. Rai et al. Zee: zero-effort crowdsourcing for indoor localization. In Proceedings of ACM MobiCom, 2012.
19. A. Schwaighofer et al. GPPS: a gaussian process positioning system for cellular networks. In Proceedings of NIPS, 2003.
20. M. Z. Shafiq et al. A first look at cellular machine-to-machine traffic: large scale measurement and characterization. In Proceedings of ACM SIGMETRICS, 2012.
21. D. Shepard. A two-dimensional interpolation function for irregularlyspaced data. In Proceedings of 23rd ACM National Conference, 1968.
22. G. Sun et al. Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs. IEEE Signal Processing Magazine, 22(4): 12-23, 2005.
23. A. Varshavsky et al. Are GSM phones THE solution for localization? In Proceedings of MCSA, IEEE Workshop on, 2006.
24. H. Wang et al. No need to war-drive: unsupervised indoor localization. In Proceedings of ACM MobiSys, 2012.
25. C. Wu et al. WILL: Wireless indoor localization without site survey. Parallel and Distributed Systems, IEEE Transactions on, 24(4): 839-848, 2013.
26. Z.-l. Wu et al. Location estimation via support vector regression. Mobile Computing, IEEE Transactions on, 6(3): 311-321, 2007.
27. Z. Yang, C. Wu, and Y. Liu. Locating in fingerprint space: wireless indoor localization with little human intervention. In Proceedings of ACM MobiCom, 2012.
28. H. Zang, F. Baccelli, and J. Bolot. Bayesian inference for localization in cellular networks. In Proceedings of IEEE Infocom, 2010.