Wi-Fi based Indoor Localization using Channel State Information

Authors

  • Mehul Vala  Assistant Professor, Electronics & Communication Department, Shantilal Shah Engineering College, Bhavnagar, Gujarat, India
  • Jignesh Bhut  Assistant Professor, Electronics & Communication Department, Shantilal Shah Engineering College, Bhavnagar, Gujarat, India

Keywords:

RSSI, CSI, Localization, Indoor, Wi-Fi.

Abstract

Indoor positioning systems are becoming increasingly popular because they enable location-based services in indoor environments. GPS is not effective for indoor positioning because its performance degrades in urban areas, around walls and buildings, and indoors. The strength of the GPS signal is very low in indoors, making it ineffective. Wi-Fi technology has emerged as a cost-effective and widely available solution for indoor positioning due to its ubiquity. This research paper presents Wi-Fi-based indoor localization method that leverage Channel State Information (CSI) for enhanced accuracy and reliability. We explore the theoretical foundations, practical implementation, and experimental results of using CSI for indoor localization. The proposed methodology demonstrates promising results in real-world indoor environments.

References

  1. C. Di Flora, M. Ficco, S. Russo, and V. Vecchio, “Indoor and outdoor location based services for portable wireless devices,” in 25th IEEE International Conference on Distributed Computing Systems Workshops, 2005, pp. 244–250.
  2. D. Zhang, F. Xia, Z. Yang, L. Yao, and W. Zhao, “Localization technologies for indoor human tracking,” in 2010 5th international conference on future information technology, 2010, pp. 1–6.
  3. H. Koyuncu and S. H. Yang, “A survey of indoor positioning and object locating systems,” IJCSNS Int. J. Comput. Sci. Netw. Secur., vol. 10, no. 5, pp. 121–128, 2010.
  4. V. Honkavirta, T. Perala, S. Ali-Loytty, and R. Piché, “A comparative survey of WLAN location fingerprinting methods,” in 2009 6th workshop on positioning, navigation and communication, 2009, pp. 243–251.
  5. Y. Gu, A. Lo, and I. Niemegeers, “A survey of indoor positioning systems for wireless personal networks,” IEEE Commun. Surv. \& tutorials, vol. 11, no. 1, pp. 13–32, 2009.
  6. Z. Farid, R. Nordin, M. Ismail, and others, “Recent advances in wireless indoor localization techniques and system,” J. Comput. Networks Commun., vol. 2013, 2013.
  7. Banerjee, D. Maas, M. Bocca, N. Patwari, and S. Kasera, “Through Wall People Localization Exploiting Radio Windows,” arXiv Prepr. arXiv1307.7233, 2013.
  8. Y. Liu, Z. Yang, and X. Wang, “Location, localization, and localizability,” J. Comput. Sci. Technol., vol. 25, no. 2, pp. 247–297, 2010.
  9. J. Liu, Y. Zhang, and F. Zhao, “Robust distributed node localization with error management,” in Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing, 2006, pp. 250–261.
  10. D. Halperin, W. Hu, A. Sheth, and D. Wetherall, “Tool release: Gathering 802.11 n traces with channel state information,” ACM SIGCOMM Comput. Commun. Rev., vol. 41, no. 1, p. 53, 2011.
  11. K. Heurtefeux and F. Valois, “Is RSSI a good choice for localization in wireless sensor network?,” in 2012 IEEE 26th international conference on advanced information networking and applications, 2012, pp. 732–739.
  12. S.-H. Fang, T.-N. Lin, and K.-C. Lee, “A novel algorithm for multipath fingerprinting in indoor WLAN environments,” IEEE Trans. Wirel. Commun., vol. 7, no. 9, pp. 3579–3588, 2008.
  13. C. Beder and M. Klepal, “Fingerprinting based localisation revisited: A rigorous approach for comparing RSSI measurements coping with missed access points and differing antenna attenuations,” in 2012 international conference on indoor positioning and indoor navigation (IPIN), 2012, pp. 1–7.
  14. Siddig, A. Makki, and C. Bleakley, “Lighthouse: Precise 802.11-based localization,” in International Conference on Indoor Positioning and Indoor Navigation, 2013, pp. 1–6.
  15. M. Youssef and A. Agrawala, “The Horus WLAN location determination system,” in Proceedings of the 3rd international conference on Mobile systems, applications, and services, 2005, pp. 205–218.
  16. L. Hanzo, Y. Akhtman, L. Wang, and M. Jiang, MIMO-OFDM for LTE, WiFi and WiMAX: Coherent versus non-coherent and cooperative turbo transceivers, vol. 9. John Wiley \& Sons, 2010.
  17. M. Jiang and L. Hanzo, “Multiuser MIMO-OFDM for next-generation wireless systems,” Proc. IEEE, vol. 95, no. 7, pp. 1430–1469, 2007.
  18. D. Tse, Fundamentals of Wireless Communication12. 2004.
  19. D. Halperin, W. Hu, A. Sheth, and D. Wetherall, “Predictable 802.11 packet delivery from wireless channel measurements,” ACM SIGCOMM Comput. Commun. Rev., vol. 40, no. 4, pp. 159–170, 2010.
  20. D. Halperin, W. Hu, A. Sheth, and D. Wetherall, “802.11 with multiple antennas for dummies,” ACM SIGCOMM Comput. Commun. Rev., vol. 40, no. 1, pp. 19–25, 2010.

International Journal of Scientific Research in Science and Technology

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Published

2017-01-30

Issue

Volume 3, Issue 1, January-February-2017

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Mehul Vala, Jignesh Bhut, " Wi-Fi based Indoor Localization using Channel State Information, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 1, pp.886-893, January-February-2017.