RF-Powered Cognitive Radio Networks: Technical Challenges and Limitations

The increasing demand for spectral and energy efficient communication networks has spurred a great interest in energy harvesting (EH) cognitive radio networks (CRNs). Such a revolutionary technology represents a paradigm shift in the development of wireless networks, as it can simultaneously enable the efficient use of the available spectrum and the exploitation of radio frequency (RF) energy in order to reduce the reliance on traditional energy sources. This is mainly triggered by the recent advancements in microelectronics that puts forward RF energy harvesting as a plausible technique in the near future. On the other hand, it is suggested that the operation of a network relying on harvested energy needs to be redesigned to allow the network to reliably function in the long term. To this end, the aim of this survey paper is to provide a comprehensive overview of the recent development and the challenges regarding the operation of CRNs powered by RF energy. In addition, the potential open issues that might be considered for the future research are also discussed in this paper.Comment: 8 pages, 2 figures, 1 table, Accepted in IEEE Communications Magazin

Spectrum Sensing Framework based on Blind Source Separation for Cognitive Radio Environments

El uso eficiente del espectro se ha convertido en un área de investigación activa, debido a la escasez de este recurso y a su subutilización. En un escenario en el que el espectro es un recurso compartido como en la radio cognitiva (CR), los espacios sin uso dentro de las bandas de frecuencias con licencia podrían ser detectados y posteriormente utilizados por un usuario secundario a través de técnicas de detección y sensado del espectro. Generalmente, estas técnicas de detección se utilizan a partir de un conocimiento previo de las características de canal. En el presente trabajo se propone un enfoque de detección ciega del espectro basado en análisis de componentes independientes (ICA) y análisis de espectro singular (SSA). La técnica de detección se valida a través de simulación, y su desempeño se compara con metodologías propuestas por otros autores en la literatura. Los resultados muestran que el sistema propuesto es capaz de detectar la mayoría de las fuentes con bajo consumo de tiempo, un aspecto que cabe resaltar para aplicaciones en línea con exigencias de tiempo.The efficient use of spectrum has become an active research area, due to its scarcity and underutilization. In a spectrum sharing scenario as Cognitive Radio (CR), the vacancy of licensed frequency bands could be detected by a secondary user through spectrum sensing techniques. Usually, this sensing approaches are performed with a priori knowledge of the channel features. In the present work, a blind spectrum sensing approach based on Independent Component Analysis and Singular Spectrum Analysis is proposed. The approach is tested and compared with other outcomes. Results show that the proposed scheme is capable of detect most of the sources with low time consumption, which is a remarkable aspect for online applications with demanding time issues