Manuscript Title:

IMPROVED GENETIC GAUSSIAN ADAPTIVE APPROACH USING ML FOR PAPR REDUCTION IN 6G APPLICATIONS

Author:

RAMARAO BODDU, Dr. LATHA B M, Dr. A.V.SUBBARAO

DOI Number:

DOI:10.17605/OSF.IO/MY8XU

Published : 2022-09-23

About the author(s)

1. RAMARAO BODDU - Research Scholar, Dep. of ECE, VTU, Belgavi, Karnataka & Assoc. Prof, Dept. of ECE, Amrita Sai Institute of Science and Technology, Paritala, Vijayawada, Andhra Pradesh
2. Dr. LATHA B M - Professor, GM Institute of Technology, Daveneger, Karnataka.
3. Dr. A.V.SUBBARAO - Professor, Dept. of ECE, Newtons Inst. of Science & Technology, Macherla, AP.

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Abstract

With the advent of Network power reduction capabilities in mobile communication have impacted the design that could sustain the latest model design in communication trends. One such feature is PAPR for the mobile communications that have to be reduced while implementing the network model for communication. Most techniques in recent trends in MC have effects the PAPR reduction values less than 10. This paper improvises a novel PAPR reduction filter and optimization characteristic using ISGA for 5G + with improved PAPR values as tabulated. The ISGA algorithm on the OFDM would implicate the power calculation based on mathematical analysis for PAPR. This paper also compares with other existed techniques such as SLM, PTS and clipping.


Keywords

Orthogonal Frequency division multiplexing (OFDM), forward error correction (FEC), Filtered Orthogonal Frequency Division Multiplexing (F- OFDM), Peak to Average Power Ratio (PAPR), Long Term Evolution (LTE), selective mapping (SLM), Partial Transit Scheme (PTS), IGMSGA (Improved Genetic Model using Stochastic Gaussian Approach).