Wireless Sensor Node Localization based on LNSM and Hybrid TLBO- Unilateral technique for Outdoor Location

Vivek Kaundal, Paawan Sharma, Manish Prateek


The paper aims at localization of the anchor node
(fixed node) by pursuit nodes (movable node) in outdoor location.
Two methods are studied for node localization. The first method
is based on LNSM (Log Normal Shadowing Model) technique to
localize the anchor node and the second method is based on Hy-
brid TLBO (Teacher Learning Based Optimization Algorithm)-
Unilateral technique. In the first approach the ZigBee protocol
has been used to localize the node, which uses RSSI (Received
Signal Strength Indicator) values in dBm. LNSM technique is
implemented in the self-designed hardware node and localization
is studied for Outdoor location. The statistical analysis using
RMSE (root mean square error) for outdoor location is done and
distance error found to be 35 mtrs. The same outdoor location
has been used and statistical analysis is done for localization
of nodes using Hybrid TLBO-Unilateral technique. The Hybrid-
TLBO Unilateral technique significantly localizes anchor node
with distance error of 0.7 mtrs. The RSSI values obtained are
normally distributed and standard deviation in RSSI value is
observed as 1.01 for outdoor location. The node becomes 100%
discoverable after using hybrid TLBO- Unilateral technique.

Full Text:



Guerriero, M., et al., Some aspects of DOA estimation using a network of blind sensors. Signal Processing, 2008. 88(11): p. 2640-2650.

Singh, S.P. and S. Sharma, Range free localization techniques in wireless sensor networks: A review. Procedia Computer Science, 2015. 57: p. 7-16.

Doherty, L. and L. El Ghaoui. Convex position estimation in wireless

sensor networks. in INFOCOM 2001. Twentieth Annual Joint Conference

of the IEEE Computer and Communications Societies. Proceedings.

IEEE. 2001. IEEE.

Bulusu, N., J. Heidemann, and D. Estrin, GPS-less low-cost outdoor

localization for very small devices. IEEE personal communications, 2000.

(5): p. 28-34.

He, T., et al. Range-free localization schemes for large scale sensor

networks. in Proceedings of the 9th annual international conference on

Mobile computing and networking. 2003. ACM.

Almuzaini, K.K. and T.A. Gulliver. A new distributed range-free localization algorithm for wireless networks. in Vehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th. 2009. IEEE.

Aiello, M., R. de Jong, and J. de Nes. Bluetooth broadcasting: How far

can we go? An experimental study. in Pervasive Computing (JCPC), 2009

Joint Conferences on. 2009. IEEE.

Specification, Z., ZigBee Alliance. ZigBee Document 053474r06, Ver-

sion, 2006. 1.

Chruszczyk, . and A. Zajc, Comparison of indoor/outdoor, RSSI-based positioning using 433, 868 or 2400 MHz ISM bands. International Journal of Electronics and Telecommunications, 2016. 62(4): p. 395-399.

Rao, R.V., Teaching-Learning-Based Optimization Algorithm, in Teaching Learning Based Optimization Algorithm2016, Springer. p. 9-39.

Vivek Kaundal, Paawan Sharma, Devender Saini, Manish Prateek,

Location Fingerprinting Supported Unilateral Algorithm based on Experi-

mental Study of Localization in Disaster Prone Area International Journal

of Computer Science and Information Security, 2016. 14: p. 162-175.

Halder, S. and A. Ghosal, A survey on mobility-assisted localization

techniques in wireless sensor networks. Journal of Network and Computer Applications, 2016. 60: p. 82-94.

He, T., et al., Range-free localization and its impact on large scale sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 2005. 4(4): p. 877-906.

Anzai, D. and S. Hara. An RSSI-based MAP localization method with

channel parameters estimation in wireless sensor networks. in Vehicular

Technology Conference, 2009. VTC Spring 2009. IEEE 69th. 2009. IEEE.

Cheng, G., Accurate TOA-based UWB localization system in coal mine based on WSN. Physics Procedia, 2012. 24: p. 534-540.

Dakkak, M., et al., Indoor localization method based on RTT and AOA using coordinates clustering. Computer networks, 2011. 55(8): p. 1794-1803.

Gezici, S., A survey on wireless position estimation. Wireless personal communications, 2008. 44(3): p. 263-282.

Gharghan, S.K., et al., Accurate Wireless Sensor Localization Technique Based on Hybrid PSO-ANN Algorithm for Indoor and Outdoor Track Cycling. IEEE Sensors Journal, 2016. 16(2): p. 529-541.

Pires, R.P., et al., Evaluation of an rssi-based location algorithm for

wireless sensor networks. IEEE Latin America Transactions, 2011. 9(1):

p. 830-835.

Blywis, B., et al. A localization framework for wireless mesh networks anchor-free distributed localization in the des-testbed. in Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on. 2010. IEEE.

Huang, C.-N. and C.-T. Chan, ZigBee-based indoor location system by k-nearest neighbor algorithm with weighted RSSI. Procedia Computer

Science, 2011. 5: p. 58-65.

Liu, W., et al. Radio map position inference algorithm for indoor

positioning systems. in 2012 18th IEEE International Conference on

Networks (ICON). 2012. IEEE.

Luo, X., W.J. OBrien, and C.L. Julien, Comparative evaluation of Re-

ceived Signal-Strength Index (RSSI) based indoor localization techniques

for construction jobsites. Advanced Engineering Informatics, 2011. 25(2): p. 355-363.

Mao, G., B. Fidan, and B.D. Anderson, Wireless sensor network

localization techniques. Computer networks, 2007. 51(10): p. 2529-2553.

Meng, W., L. Xie, and W. Xiao, Decentralized TDOA sensor pairing

in multihop wireless sensor networks. IEEE Signal Processing Letters,

20(2): p. 181-184.

Mesmoudi, A., M. Feham, and N. Labraoui, Wireless sensor net-

works localization algorithms: a comprehensive survey. arXiv preprint

arXiv:1312.4082, 2013.

Nasipuri, A. and K. Li. A directionality based location discovery scheme for wireless sensor networks. in Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications. 2002. ACM.

Savvides, A., C.-C. Han, and M.B. Strivastava. Dynamic fine-grained

localization in ad-hoc networks of sensors. in Proceedings of the 7th

annual international conference on Mobile computing and networking.


Hanusz, Z., J. Tarasinska, and W. Zielinski, Shapiro-Wilk test with

known mean. REVSTAT-Statistical Journal, 2016. 14(1): p. 89-100.

Thadewald, T. and H. Bning, JarqueBera test and its competitors for

testing normalitya power comparison. Journal of Applied Statistics, 2007.

(1): p. 87-105.


  • There are currently no refbacks.

International Journal of Electronics and Telecommunications
is a periodical of Electronics and Telecommunications Committee
of Polish Academy of Sciences

eISSN: 2300-1933