Distributed sensor localization under communication constraints

This paper proposes an improved algorithm named DLRE-Q with a uniform quantizer for distributed sensor localization under communication constraints. Firstly, a relaxation parameter is introduced into the DILOC algorithm and embedded with a uniform quantizer. The quantization error is modeled as a bounded random variable, resulting in a communication-efficient distributed update equation where each sensor only needs to communicate withm+ 1 neighbors. Furthermore, based on Lyapunov stability theory, it is rigorously proven that the estimation error of DLRE-Q converges to zero almost surely. Simulations in a two-dimensional sensor network demonstrate that a smaller quantization step size leads to higher localization accuracy, and the convergence rate remains unaffected.