Weighted Centroid Correction Localization in Cellular Systems

Abstract

Problem statement:There is a large demand for wireless Location-Based Service (LBS) and it is provided by many wireless cellular systems. In process of positioning a Mobile Station (MS), the computing speed is as important as the positioning accuracy and the algorithm should also be resistant to environmental influences. Approach: A new positioning method based on Weighted Centroid Correction Localization (WCCL) for wireless cellular systems is introduced in this article. Firstly, referring to the receiving-state of an MS in cellular systems, it computes a weighted centroid of surrounding Base Stations (BSs) as a rough approximate position of the MS. Then, according to the distances between the MS and the BSs being less or bigger than the computed distances between the BSs and the weighted centroid, it corrects the coordinate of the weighted centroid towards the directions of the BSs by moving it closer or farther in turn. Results: According to our experiments, WCCL improves the positioning accuracy, as well as to provide a better resistance to environmental influences. Conclusion: As a modified centroid-based localization algorithm, WCCL obtains weighting factors from the receiving-state of MS in multi-cells structured cellular systems and obtains a better positioning result in cellular systems without updating the network equipment. Therefore, for the cellular positioning problem, WCCL algorithm can be an alternate solution.

A Novel Hybrid Node Localization Algorithm for Wireless Sensor Networks

“…There are also NLAs that belong to both classes because they use the content of the received messages and distances/angles. These are referred to as hybrid NLAs; e.g., the Triangular Centroid Localization Algorithm (Jauregui-Ortiz et al, 2011), Weighted Centroid Localization (Blumenthal et al, 2007), Sequential Greedy Optimization based Localization Algorithm (Shi et al, 2010), Weighted centroid correction localization (Li et al, 2011) and Improved Centroid Localization (Liu et al, 2012). However, the integration of a large amount of factors into a NLA is not related directly to a high accuracy.…”