The generalized frequency division multiplexing (GFDM) system has attracted the interest of the research community due to its unique characteristics such as high spectrum efficiency, low latency, and high transmission rate. However, like every multicarrier technique superimposition of a number of subsymbols in the time domain results in a high peak-to-average power ratio (PAPR). In general, the PAPR reduction system in the literature increases the average power while decreasing the PAPR which is not a plausible solution for practical 5G applications. In order to address this issue, we propose an efficient PAPR reduction strategy that maintains the PAPR without increasing the average power. In this method, an optimal orthogonal precoding matrix based on singular value decomposition (SVD) is designed to reduce the system's average power. Because this optimal precoding matrix cannot successfully reduce the PAPR, we introduce a second technique called peak samples affixing to minimize both the peak and average power. For the proposed method's assessment, using LabVIEW software and the universal software radio peripheral 2953R (USRP) as hardware, we developed an experimental setup to enable real-time transmission. The received spectral response from USRP authenticated the proposed method by showing a good agreement with simulations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.