ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2016, Vol. 53 ›› Issue (1): 216-227.doi: 10.7544/issn1000-1239.2016.20148087

Previous Articles    

Localization Algorithm for Wireless Sensor Networks via Norm Regularized Matrix Completion

Xiao Fu1,2,3, Sha Chaoheng1, Chen Lei1,2, Sun Lijuan1,2,3, Wang Ruchuan1,2,3   

  1. 1(School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003); 2(Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks (Nanjing University of Posts and Telecommunications), Nanjing 210003); 3(Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education, Nanjing 210003)
  • Online:2016-01-01

Abstract: Localization is one of the important preconditions for wireless sensor networks (WSNs) applications.Traditional range-based localization algorithms need large amounts of pair-wise distance measurements between sensor nodes.However, noise and data missing are inevitable in distance ranging, which may degrade localization accuracy drastically. To address this challenge, a novel localization algorithm for WSNs based on L1-norm regularized matrix completion (L1NRMC) is proposed in this paper. By utilizing the natural low rank feature of the Euclidean distance matrix (EDM) between nodes, the recovery of partly sampled noisy distance matrix is formulated as an L1-norm regularized matrix completion problem, which is solved by alternating direction method of multipliers (ADMM) and operator splitting technology.Based on the reconstructed EDM, the classical MDS-MAP algorithm is applied to obtain the coordinates of all the unknown nodes.This algorithm can not only detect and remove outliers, but also smooth the common Gaussian noise implicitly. Simulation results demonstrate that compared with traditional node localization algorithms, our algorithm achieves high accuracy from only small fraction of distance measurements and resists various types of ranging noise, which makes our algorithm suitable for resource-limited WSNs.

Key words: wireless sensor networks (WSNs), localization, outlier, matrix completion, L1-norm regularization

CLC Number: