2020 28th European Signal Processing Conference (EUSIPCO) | 2021
Graph Learning and Augmentation Based Interpolation of Signal Strength for Location-Aware Communications
Abstract
A graph learning and augmentation (GLA) technique is proposed herein to solve the received signal power interpolation problem, which is important for preemptive resource allocation in location-aware communications. A graph parameterization results in the proposed GLA interpolator having superior mean-squared error performance and lower computational complexity than the traditional Gaussian process method. Simulation results and analytical complexity analysis are used to prove the efficacy of the GLA interpolator.