Optimal Techniques for Sensing Error Minimization with Improved Energy Detection in Cognitive Radios

Spectrum sensing, the problem of detecting the presence of licensed user in the channel is considered in this paper. Energy detection is best suited for the spectrum sensing when prior knowledge about the primary users is unavailable. Existing works report improved versions of energy detection which primarily focuses on maximizing the detection performance. Sensing error minimization is an important aspect of spectrum sensing that needs attention. This paper focuses on the sensing error minimization of the improved energy detection algorithm in which the decision statistic is computed using an arbitrary positive index instead of squaring operation. First, an optimum decision threshold satisfying Minimum Error Bound (MEB) is derived. Next, an optimum value of the arbitrary positive index with minimum number of samples satisfying a Target Error Bound (TEB) is derived. A thorough numerical analysis and simulations are performed and the results confirm the accuracy of the analysis.