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Quantized lower bounds on grid-based localization algorithm for wireless sensor networks

Lookup NU author(s): Aws Al-Qaisi, Professor Bayan Sharif, Dr Charalampos TsimenidisORCiD, Professor Jeffrey Neasham


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In this paper, we introduce a Quantized Cramer Rao Bound (Q-CRB) method, which adapts the use of the CRB to handle grid-based localization algorithms with certain constraints, such as localization boundaries. In addition, we derive a threshold granularity level which identifies where the CRB can be appropriately applied to this type of algorithm. Moreover, the derived threshold value allows the users of grid-based LSE techniques to probably avoid some unnecessary complexities associated with using high grid resolutions. To examine the feasibility of the new proposed bound, the grid-based least square estimation (LSE) technique was implemented. The Q-CRB was used to evaluate the performance of the LSE method under extensive simulation scenarios. The results show that the Q-CRB provided a tight bound in the sense that the Q-CRB can characterize the behaviour of location errors of the LSE technique at various system parameters, e.g. granularity levels, measurement accuracies, and in the presence or absence of localization boundaries.

Publication metadata

Author(s): Al-Qaisi A, Alhasanat AI, Mesleh A, Sharif BS, Tsimenidis CC, Neasham JA

Publication type: Article

Publication status: Published

Journal: Annals of Telecommunications

Year: 2016

Volume: 71

Issue: 5-6

Pages: 239-249

Print publication date: 01/06/2016

Online publication date: 11/03/2016

Acceptance date: 11/02/2016

ISSN (print): 0003-4347

ISSN (electronic): 1958-9395

Publisher: Springer


DOI: 10.1007/s12243-016-0494-y


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