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

Aws Al-Qaisi, A. I. Alhasanat, Abdelwadood Mesleh, B. S. Sharif, C. C. Tsimenidis, J. A. Neasham

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


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.

Original languageBritish English
Pages (from-to)239-249
Number of pages11
JournalAnnales des Telecommunications/Annals of Telecommunications
Issue number5-6
StatePublished - 1 Jun 2016


  • Grid-based localization
  • Localization
  • Wireless sensor networks
  • WSN


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