A Hybrid Solution Analysis with IFDMA to Optimizing the Response of the Dense Layers | [International Journal of Communication Networks and Information Security • 2024]

Author(s):

1. Ramarao Boddu: Dep. of ECE, VTU,Belgavi, Karnataka,India

2. Latha B M: Department of ECE, Jain Institute of Technology, Dawanagere, India

Abstract:

In current trends in wireless communication power reduction and capabilities plays major role in detection or estimating the overall consumption at receiver or transmitter. Peak values and mean values or average values in power reduction with in the range of 0-7dB for next generation communication such as 5g, 5g+ or ever 6G. With regards of the power in current mobile communication technologies PAPR feature is still specifying its importance with massive communication domains. To reduce the overall problem of PAPR values for every phased response or frequency ones indicates a solution that have to be realized for effective design in Wireless Network. In order to implement such system, OFDM, LFDMA, IFDMA and other learning models with SLM-OFDM, PSO-OFDM …. etc. In this paper, we introduce a hybrid solution analysis with IFDMA with Hybrid CNN with LSTM structure with more than 9-layers of dense layers indicating the overall optimization response of the Dense layers for the observed optimized design. To realize such problem, we introduce a communication model with very good spectral behaviour and BER performance. With simulation result we demonstrate IDDM algorithm have been shown improved results with PAPR reduction of 4.5 to 6 dB variation based on “ ” factors for every simulation response.

Page(s): 1-106

DOI: DOI not available

Published: Journal: International Journal of Communication Networks and Information Security, Volume: 16, Issue: 3, Year: 2024

Keywords:

Particle swarm optimization PSO , Support Vector Machine , Convolutional Neural Network CNN , Peak Average Power Ratio , Random Forest Classifier

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