Sensado de espectro local de banda ancha para radios cognitivos multi-antena basado en compleción de matrices y muestreo sub-nyquist uniforme en el dominio disperso

Abstract

This article addresses the problem of spectrum local broadband sensing by Cognitive Radio of multiple antennas, based on matrix completion and uniform sub-Nyquist sampling in sparse domain. In the wideband environment, one of the biggest problems for spectrum sensing is the large number of samples to be processed when a multiband signal is sampled at or above the Nyquist rate. This generates large detection times, high-energy consumptions and the need for high processing capabilities in Cognitive Radio Devices. The simulation results show that the proposed method allows the efficient sensing of spectrum, improving performance sensing.