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13-12-2018 | Focus | Issue 8/2019

Soft Computing 8/2019

A novel PTS: grey wolf optimizer-based PAPR reduction technique in OFDM scheme for high-speed wireless applications

Journal:
Soft Computing > Issue 8/2019
Authors:
R. S. Suriavel Rao, P. Malathi
Important notes
Communicated by P. Pandian.

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Abstract

OFDM in high-speed wireless applications is an essential signal processing technique for the forthcoming decades due to its high-speed compatibility. The demand for high-speed applications increases due to availability of limited bandwidth source. Not only wired applications but also wireless applications usage increases day by day as emerging trends innovate new devices. These results in high data rate requirement and hence increase in number of sub-carriers. This creates issue with the peak-to-average power ratio (PAPR). The major challenge on such OFDM is to provide a better system performance by reducing the PAPR. Many reduction models are available in research market, such as selected mapping and clipping. The proposed research model employs partial transmit sequence which uses phase factor along with a meta-heuristic optimization algorithm for improved results. This optimization provides low complex and fast convergence qualities with data classification, and it is better than nature-inspired optimization algorithms. Experiment results are compared, and it is observed that our proposed grey wolf optimization algorithm has better efficiency than the existing optimization algorithms.

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