Localization of Internet of Things network via Euclidean distance matrix completion

In this paper, we propose a matrix completion algorithm to acquire the sensor map of Internet of Things (IoT) network. Our approach consists of two main steps to reconstruct Euclidean distance matrix. Firstly, we formulate the Euclidean distance matrix completion problem as an unconstrained optimization in smooth Riemannian manifold. We next employ nonlinear conjugate gradient algorithm on this manifold to solve the matrix completion problem. From the numerical experiments, we show that the proposed algorithm is effective recovering the distance matrix accurately with much smaller measurement than that required by conventional approaches and also outperforms the state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.