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PAPR analysis of OFDM system using AI based multiple signal representation methods

Journal from gdlhub / 2020-01-09 11:26:44
By : Jyoti Shukla, Alok Joshi, Rajesh Tyagi, Telkomnika
Created : 2020-01-09, with 1 files

Keyword : ABC, DE, PAPR, PTS, PSO
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/issue/view/640
Document Source : web

OFDM (orthogonal frequency division multiplexing) is widely used in 4th generation applications

owing to its robustness in fading environments. The major issues with OFDM systems is the high PAPR

(peak-to-average power ratio) of the transmitted signals, it leads to in and out of band distortion. SLM

(selective mapping) and PTS (partial transmit sequence) are two key methods for PAPR reduction. Both

the methods require exhaustive searching of phase factors to optimize the PAPR, these searches lead to

high computational complexity. This paper discusses using optimization based PAPR reduction methods

which an be used with PTS for the reduction of computational complexity and search space. In this paper

we have analyzed PTS and SLM with particle swarm optimization (PSO), Artificial Bee Colony (ABC) and

differential evolution (DE). PAPR and BER (bit error rate) comparison is done for both the cases.

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