Rician statistical assumptions for geographic routing in wireless sensor networks. (1st August 2015)

• Record Type: Journal Article
• Authors: Popescu, Ana Maria; Salman, Naveed; Kemp, Andrew H.
• Is Part Of: IET wireless sensor systems. Volume 5:Number 4(2015)
• Page Start: 204
• Page End: 209
• Publication Date: 2015-08-01
• Subjects: Gaussian distribution -- telecommunication network routing -- wireless sensor networks -- sensor placement -- RSSI -- least squares approximations; target sensor node position estimation -- linear least square method -- received signal strength‐based localisation -- Rician hypothesis -- Gaussian distributed location error statistical assumption -- wireless sensor network -- geographic routing -- Rician statistical assumption; Wireless sensor networks -- Periodicals; 681.2
• DOI: 10.1049/iet-wss.2014.0023
• Languages: English
• ISSNs: 2043-6386

Abstract

Abstract : Geographic routing algorithms for wireless sensor networks need to be resilient to the inherent location errors of positioning systems. Proposed forwarding algorithms in the literature make use of the statistical assumption of Gaussian distributed location error and Ricianly distributed distance estimates between sensor nodes. In this study, the validity of the Rician hypothesis when realistic localisation is employed and simulated is analysed. The authors consider received signal strength‐based localisation through the linear least square method. Anchor nodes estimate the position of the target sensor nodes as well as their error characteristics, which are no longer assumed Gaussian. Both theoretical and simulation results confirm that the Rician assumption is not true when realistic localisation scenarios are used, affecting the performance of geographic routing algorithms based on this statistical supposition.