Spectrum situation generation from sparse spatial sampling: model and algorithm

Abstract

With the increasingly complex electromagnetic spectrum environment and the growing demand for the available spectrum, it is urgent to mine the spectrum situation information of wide geographical areas from limited sensing nodes to maintain the order and security of the electromagnetic spectrum and improve the overall utilization efficiency of spectrum resources. Starting from the multidimensional representations of spectrum situations in time, frequency, and space, this paper discusses and summarizes the model and generation mechanisms of electromagnetic spectrum situations based on sparse spatial sampling. The spectrum situation representation method based on a multivariate function is proposed, and the spectrum situation model, in accordance with the propagation characteristics of different transmitters, is established. This paper analyzes the identifiability and recoverability conditions of the spectrum situation model under sparse spatial sampling, which theoretically guides the reliable generation of the spectrum situation. Finally, the performance characteristics of different spectrum situation generation algorithms are compared and analyzed by simulations.