Abstract
Modulation categorization, which is a significant duty performed by smart receivers, is critical for applications in both the military and civilian sectors. This research topic has been intensively investigated for single-hop wireless communications. However, there are a few studies that concentrate on multiple hop communications systems. In this paper, we design a novel autonomous modulation categorization technique for amplify-and-forward relaying systems. Analytical formulations of correlation functions used as the foundation of the proposed method are developed. By exploiting the spatial redundancy, we theoretically demonstrate that a set of modulation forms produces peaks for particular correlation functions whereas the other set does not. We design a multiple-level hypothesis assessment for judgment based on this property. The suggested approach has the benefit of not requiring channel coefficients or noise power information. Computer simulations are conducted to test the proposed method's categorization performance. The findings demonstrate that the suggested method produces appropriate results under various operating situations. The suggested approach reaches an accuracy of about one hundred percent when the SNR is 10 dB or higher. On the other hand, the traditional algorithms fail to provide acceptable performance even at high SNR.