Low Power Wideband Sensing for One-Bit Quantized Cognitive Radio Systems

Wideband Spectrum Sensing for Cognitive Radio Networks

Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is wideband spectrum sensing: secondary users reliably detect spectral opportunities across a wide frequency range. In this article, various wideband spectrum sensing algorithms are presented,...

Low-Power Spectrum Sensing for Cognitive Radio Applications

Cooperative Wideband Spectrum Sensing for the Centralized Cognitive Radio Network

Various primary user (PU) radios have been allocated into fixed frequency bands in the whole spectrum. A cognitive radio network (CRN) should be able to perform the wideband spectrum sensing (WSS) to detect temporarily unoccupied frequency bands. We summarize four occupancy features for the frequency bands. 1. The occupancy is sparse; 2. The frequency band allocation information is fixed and co...

Anti-sampling-distortion compressive wideband spectrum sensing for Cognitive Radio

Too high sampling rate is the bottleneck to wideband spectrum sensing for cognitive radio in mobile communication. Compressed sensing (CS) is introduced to transfer the sampling burden. The standard sparse signal recovery of CS does not consider the distortion in the analogue-to-information converter (AIC). To mitigate performance degeneration casued by the mismatch in least square distortionle...

A novel reduced power compressive sensing technique for wideband cognitive radio

Wideband spectrum sensing for cognitive radio requires high rate analog to digital (A/D) converters whose power consumption is proportional to the sampling rate. In this article, we propose to use sub-Nyquist non-uniform sampling for spectrum sensing to reduce the power consumption. Since the received signal samples are correlated in the time domain, we estimate the missing samples by using the...