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Hybrid PS–GW optimised PTS scheme for PAPR reduction in OFDM system
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The most famous and attractive strategy used in wireless communication for huge transmission of data with higher rate was orthogonal frequency division multiplexing (OFDM) approach. Efficient methods are important for PAPR reduction in high‐speed wireless communication systems. The reduction of PAPR in OFDM system has been carried out with one of the most familiar approach called Partial transmit sequences (PTS). Various techniques are already presented for reducing the PAPR, some of them are, clipping, SLM, and PTS. From that PTS is considered as an efficient method because the PAPR was reduced by PTS without causing any signal distortion. In this work, PTS along with hybridization optimization algorithm named as PS–GW will be implemented to get the minimum performance on PAPR and computational complexity. The PS–GW is a combination of both the Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) which search the optimal combination of phase rotational factors efficiently. A fundamental thought in this method was that the capacity of exploitation in PSO was enhanced with the capacity of investigation in GWO to create a two variations in quality. The results produced by this proposed method shows that the reduction was effectively determined in both PAPR and computational complexity.
Institution of Engineering and Technology (IET)
Title: Hybrid PS–GW optimised PTS scheme for PAPR reduction in OFDM system
Description:
The most famous and attractive strategy used in wireless communication for huge transmission of data with higher rate was orthogonal frequency division multiplexing (OFDM) approach.
Efficient methods are important for PAPR reduction in high‐speed wireless communication systems.
The reduction of PAPR in OFDM system has been carried out with one of the most familiar approach called Partial transmit sequences (PTS).
Various techniques are already presented for reducing the PAPR, some of them are, clipping, SLM, and PTS.
From that PTS is considered as an efficient method because the PAPR was reduced by PTS without causing any signal distortion.
In this work, PTS along with hybridization optimization algorithm named as PS–GW will be implemented to get the minimum performance on PAPR and computational complexity.
The PS–GW is a combination of both the Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) which search the optimal combination of phase rotational factors efficiently.
A fundamental thought in this method was that the capacity of exploitation in PSO was enhanced with the capacity of investigation in GWO to create a two variations in quality.
The results produced by this proposed method shows that the reduction was effectively determined in both PAPR and computational complexity.
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