Intelligent decision making with improved energy detection for precise spectrum sensing in cognitive radio

Abstract

Energy detection is best suited for the spectrum sensing when prior knowledge about the licensed user is unavailable. The performance of this technique is primarily influenced by the available test statistic, number of samples used to compute the test statistic and the decision threshold and described in terms of probability of detection and false alarm. This paper focuses on an intelligent sensing scheme with improved energy detection algorithm in which the test statistic is computed using an arbitrary positive power instead of squaring operation. The detection performance is found to be considerably improved compared to the traditional energy detection algorithm. Simulations are performed, and the results confirm the accuracy of the analysis.