Radio Map Updating from Streaming Spectrum Measurements via Memory-Based Online Gaussian Processes
A memory-based online sparse variational Gaussian process (M-OSVGP) method that efficiently updates radio maps from streaming spectrum measurements and extends M-OSVGP with a grid-assisted online inducing point selection (GOIPS) algorithm that dynamically adapts the number and locations of inducing points based on measurement density and spatial correlation.