Abstract
Machine to machine (M2M) communication is a promising technology to enhance both spectral efficiency and energy efficiency in cellular networks. To achieve those benefits, localization of unknown machine in M2M communications are crucial for several perspectives, such as power control to mitigate interference, improve energy efficiency and reduce traffic burden on the base stations (BSs). In this paper, we propose time of arrival (TOA) and time difference of arrival (TDOA) based localization techniques for M2M communications over cellular networks. The algorithm estimates the location of unknown machine using TOA and TDOA from the location information of anchor machines. Weighted least square (WLS) and maximum likelihood (ML) based localization algorithms are espoused for the proposed localization techniques. Extensive simulations are carried out for evaluating the localization performance of the proposed techniques. Besides, simulation results show that the TDOA localization technique provides higher localization accuracy.
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Karim L, Mahmoud QH, Nasser N, Anpalagan A, Khan N (2015) Localization in terrestrial and underwater sensor-based M2M communication networks: architecture, classification and challenges. Int J Commun Syst 30(4):1–28
Han G, Jiang J, Zhang C, Duong TQ, Guizani M, Karagiannidis G (2016) A survey on mobile anchor node assisted local-ization in wireless sensor networks. IEEE Commun Surv Tutor 18(3):2220–2243
Karim L, Nasser N, Mahmoud, QH, Anpalagan A, Salti T E (2015) Range-free localization approach for M2M communication system using mobile anchor nodes. J Netw Comput Appl 47(15):137–146
Han G, Zhang C, Lloret J, Shu L, Rodrigues JJPC (2014) A mobile anchor assisted localization algorithm based on regular hexagon in wireless sensor networks. Sci World J 2014(219371):1–13
Kaune R (2012) accuracy studies for TDOA and TOA localization. In: IEEE international conference on information fusion. Singapore
Sotenga P.Z, Djouani K, Kurien AM, Mwila MM (2017) Indoor localisation of wireless sensor nodes towards internet of things. In: 2017 IEEE international conference on ambient systems, networks and technologies (ANT 2017). Madeira, Portugal
Huang B, Xie L, Yang Z (2015) TDOA-based source localization with distance dependent noises. IEEE Trans Wirel Commun 14(1):468–480
Das SK, Hossain MF (2018) TDOA based localization architecture for M2M communication over cellular networks. In: Proceeding of the IEEE international conference on electrical and computer engineering (ICECE 2018). Dhaka, Bangladesh, pp 1–4
Zhang L, Deng Binwei (2009) A new range-based localization algorithm for wireless sensor networks. In: Computing, communication, control, and management (CCCM). Sanya, China, pp 111–114
Luo XL, Li W, Lin JR (2012) Geometric location based on TDOA for wireless sensor networks. ISRN Appl Mathematics 2012(710979):1–10. https://doi.org/10.5402/2012/710979
Ren J, Chen J, Bai W (2016) A new localization algorithm based on Taylor series expansion for NLOS environment. Cybern Inf Technologies 16(5):127–136
Yan Y, Wang H, Shen X, He K, Zhong X (2015) TDOA-based source collaborative localization via semidefinite relaxation in sensor networks. Int J Distrib Sens Netw 11(9):1–16
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Das, S.K., Mudi, R. (2020). Range-Based Location Estimation of Machines in M2M Communications Over Cellular Networks. In: Uddin, M., Bansal, J. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-7564-4_58
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DOI: https://doi.org/10.1007/978-981-13-7564-4_58
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