Enhancement of Indoor Localization by Path-Loss Reduction Using Modified RSSI Technique


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Abstract


Localization is one of the most challenging and important issue in wireless sensor networks (WSN), especially if cost effective approaches are demanded. Distance measurement based on RSSI (Received Signal Strength Indication) is a low cost and low complexity of the distance measurement technique, and it is widely applied in the range-based localization of the WSN. The RSS (Received Signal Strength) used to estimate the distance between an unknown node and a number of reference nodes with known co-ordinates. Location of the target node is then determined by trilateration. Log-normal shadowing model can better describe the relationship between the RSSI value and the distance. Due to the Non-line of sight and multipath transmission effects in the indoor environment, the distance error or ranging error will be large. It is a challenging task to optimize the transmission power of WSNs, in presence of path loss, because although increasing the transmission power reduces the residual energy, it also reduces the number of retransmissions required. In this paper, experimental results that are carried out to analyze the sensitivity of RSSI measurements in an indoor environment for various power levels are presented. Along with the reduction in the Distance error through improved RSSI technique, Path-loss also reduced comparatively.
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Keywords


Localization; Received Signal Strength Indicator (RSSI); Power Levels; Anchor; Path-Loss

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References


A. Savvides, C. Han, M. B. Strivastava “Dynamic fine-grained localization in ad-hoc networks of sensors”, Proceedings of the 7th Annual International Conference on Mobile Computing and Networking. New York: ACM, pp.166 – 179, 2001.

D. Niculescu, B. Nath, “Ad hoc positioning system (APS) using AOA”, in proc. of the Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies. Piscataway: IEEE, pp.1734 – 1743, 2003.

R. Peng, M. Sichitiu, “Angle of arrival localization for wireless sensor networks”, In Proc. of IEEE SECON, Reston, VA, 2006.

N. Patwari, A. Hero, “Using proximity and quantized RSS for sensor localization in wireless networks”, In Proceedings of the 2nd ACM International Conference on Wireless Sensor Networks and Applications, pp. 20–29, 2003.

Guoqiang Mao, BarisFidan, Brian D.O.Anderson,“Wireless sensor network localization techniques”, computer networks, vol.51, No.10, pp-2529-2553,2007.

Frank Reichenbach and Dirk Trimmermann, “Indoor localization with low complexity in wireless sensor networks,” IEEE International Conference on Industrial Informatics, pp 1018-1022, 2006.

A. Boukerche, H. A. B. F. Oliveira, E. F. Nakamura, A. A. F.Loureiro, ''Localization Systems for Wireless Sensor Networks'', IEEE Wireless Communications, pp. 6-12, Dec.2007.

Xiao YI,Yu LIU and Lu DENG, “ A novel environment self-adaptive localization algorithm based on RSSI for wireless sensor networks” , pp-360-363, IEEE 2010.

T. S. Rappaport, Wireless Communications : Principles and Practice, 2nd edition, Prentice Hall ,2002.

Ebenezar Jebarani, M.R., Jayanthy, T., WEED-weight enabled error detection mechanism for wireless sensor networks, (2012) International Review on Computers and Software (IRECOS), 7 (6), pp. 3211-3215.

Venkataraman, R., Pushpalatha, M., Sornalakshmi, K., Performance analysis of MAC schemes in wireless sensor networks, (2013) International Review on Computers and Software (IRECOS), 8 (12), pp. 2831-2836.

Jungang ZHENG Chengdong WU Hao CHU peng JI,“Localization algorithm based on RSSI and distance geometry constrain for wireless sensor network”,IEEE, pp-2836-2839, 2010.

HyochangAhn and Sang-Burm Rhee, “Simulation of a RSSI-Based indoor localization system using Wireless sensor network”, IEEE 2010.

htttp://www.tinyos.net

http://www.xbow.com

Guoqiang Mao, Brian D.O. Anderson and BarisFidan, “Path loss exponent estimation for wireless sensor network localization”, Science Direct, Computer networks, pp. 2467–2483, 2006.

I.F.Akyildiz,W.Su, Y.Sankarasubramaniam and E.Cayirci, “Wireless sensor network: A survey”, Computer networks,Vol 38, No 4 , pp-393-422, 2002

Shivaprakasha, K.S., Kulkarni, M., Energy efficient routing protocols for wireless sensor networks: A survey, (2011) International Review on Computers and Software (IRECOS), 6 (6), pp. 929-943.

Azimiyan, F., Kheirkhah, E., Jalali, M., Classification of routing protocols in wireless sensor networks, (2012) International Review on Computers and Software (IRECOS), 7 (4), pp. 1614-1623.

Sun, S., Zhang, Q., Chen, M., Xu, B., An evolutionary based routing protocol for clustered wireless sensor networks, (2012) International Review on Computers and Software (IRECOS), 7 (3), pp. 1380-1385.


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