Joint spectrum sensing method based on energy and covariance matrix theory

Spectrum sensing fast and accurately is the premise of cognitive radio communication systems. Energy detector (ED) is the most common way, but its performance will experience a significant loss under a small noise fluctuation. In order to improve the speed and performance, we use joint spectrum sensing detection (JSSD). With dual-threshold energy detection for the primary band, it will be zoned into three areas, and the covariance absolute value detection (CAVD) for the confused area. We simulate performance and computational complexity of these algorithms under noise certain or uncertainty. Comparing these results, it show that the JSSD as a blind detection algorithm is better than Energy detector, which has a high detection performance under a small increase in complexity.