Abstract
In this paper, an efficient and reliable feature-fusion-based modulation classification (MC) algorithm for multiple-input multiple-output (MIMO) systems is developed. It uses two higher-order cumulants of the transmitted signal streams to classify a broad set of modulation types with no prior knowledge of the channel state information. We address the problem of the soft-decision fusion for the feature-fusion-based MC algorithms for MIMO systems and introduce an optimal soft-decision fusion scheme to find the classification result. The complexity order of the proposed MC algorithm is studied in detail to demonstrate its low computation cost, and its performance is validated extensively by simulation results to show its practical effectiveness.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
