A Reputation framework with Multiple-threshold Energy Detection in Wireless Cooperative Systems

In this paper, we investigate how to select a trust-worthy Helper as a friendly jammer in a wireless cooperative system (WCS). The selected Helper sends out artificial noise to interfere with an eavesdropper. To ensure that the selected Helper is trustworthy, we design a Dirichlet reputation-based framework and adopt the reputation score to evaluate the trustworthiness of a Helper. To calculate the reputation scores, we develop an artificial noise detection method based on the energy detection with multiple thresholds. According to the multiple-threshold energy detection method, we provide ratings with multiple graded levels (e.g., good-average-bad). In the Dirichlet reputation-based framework, the graded ratings are directly expressed and reflected in the derived reputation scores. Firstly, the a posteriori reputation score is computed by combining the a priori reputation score with the new ratings. Next, a point value is assigned to each rating and the normalized reputation score is computed. Finally, we adopt the normalized reputation score to select a trustworthy Helper as a friendly jammer. Numerical results are presented to demonstrate the performance of our proposed Dirichlet reputation-based framework.