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PAPR Reduction Using Advanced Partial Transmission Scheme for 5G Waveforms

Arun Kumar1, Sumit Chakravarty2, S. Suganya3, Mehedi Masud4,*, Sultan Aljahdali4

1 Department of Electronics and Communication Engineering, JECRC University, Jaipur, 303905, INDIA
2 Department of Electrical and Computer Engineering, Kennesaw State University, GA, USA
3 Electronics and Communication Engineering, CMR Institute of Technology, Bangalore, INDIA
4 Department of Computer Science, College of Computers and Information Technology, Taif University, 11099, Saudi Arabia

* Corresponding Author:Mehedi Masud. Email: email

Computer Systems Science and Engineering 2022, 42(2), 483-492. https://doi.org/10.32604/csse.2022.022899

Abstract

The implementation of Peak Average to Power Ratio (PAPR) reduction technologies will play an important role in the regularization of Fifth Generation (5G) radio communication. PAPR reduction in the advanced waveform will be the key part of designing a 5G network for different applications. This work introduces the simulation of an Advanced Partial Transmission Sequence (A-PTS) reduction techniques for Orthogonal Frequency Division Multiplexing (OFDM) and Filter Bank Multi-Carrier (FBMC) transmission schemes. In the projected A-PTS, the FBMC signals are mapped into the number of sub-blocks and Inverse Fast Fourier transform (IFFT) is performed to estimate the high peak power in the time domain. The FBMC sub-blocks are multiplied with the phase elements to achieve an optimal PAPR value. A MATLAB 2014v simulation is used to estimate the PAPR, Bit Error Rate (BER), Error Vector Magnitude (EVM), and Modulation Error Rate (MER) performance of the proposed reduction schemes. The simulated result reveals that the performance of the projected algorithm is better than the conventional algorithms.

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Cite This Article

A. Kumar, S. Chakravarty, S. Suganya, M. Masud and S. Aljahdali, "Papr reduction using advanced partial transmission scheme for 5g waveforms," Computer Systems Science and Engineering, vol. 42, no.2, pp. 483–492, 2022. https://doi.org/10.32604/csse.2022.022899



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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