<p>Peak-to-Average Power Ratio (PAPR) reduction is a challenging task in Generalized Frequency Division Multiplexing (GFDM) systems, and it leads to in-band distortion and out-of-band distortions due to the non-linearity of the high-power amplifiers. To address the PAPR issue in GFDM systems, several methods have been employed. However, the most significant limitations of these techniques are their complex implementation and their extensive usage of control parameters. Partial Transmit Sequence (PTS) is a highly outstanding technique for PAPR reduction, but it is concerned with high complexity due to its meticulous searching phase factor. In this research, a hybrid PTS based enhanced squirrel search algorithm with a random phase sequence matrix (PTS-ESSA-RPSM) reduction model is proposed to overwhelm high PAPR problems in MIMO-GFDM systems. The dominant aspiration of our proposed approach is to attain an optimum phase sequence matrix to reduce PAPR and Computational Complexity (CC) instantaneously. The problem can be tackled by the incorporation of PTS with the proposed ESSA optimized RPSM approach to reclaim the optimal phase factor by the reduction of PAPR, CC, and faster convergence rate. The proposed method is validated with other relevant techniques by measuring Complementary Cumulative Density Function (CCDF), PAPR, and SNR by varying symbols, subcarriers, and oversampling factors. When compared to conventional methods, the proposed strategy improves PAPR by 20–50% across a range of CCDF levels, with the lowest PAPR values observed. At the CCDF <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11276_2025_3997_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="33" /> </InlineMediaObject> <EquationSource Format="TEX">$10^{ - 2}$</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mn>10</mn> <mrow> <mo>-</mo> <mn>2</mn> </mrow> </msup> </math></EquationSource> </InlineEquation>, the proposed method achieves approximately 3 dB in PAPR. Reductions in out-of-band emissions of 23–60% at various IBO levels validate the capacity of the proposed approach to reduce spectral leakage. ESSA is a very effective optimization strategy since it converges rapidly in about 100 iterations and achieves a final PAPR that is 25–62.5% lower than other optimization strategies. According to the simulation findings, it can be concluded that the proposed model minimizes PAPR very efficiently without increasing the system’s complexity.</p>

An efficient PAPR reduction by using hybrid PTS-ESSA method for MIMO-GFDM wireless system

期刊论文
发表日期：

2025年7月25日

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Relangi Anil Kumar,
K. Satya Prasad

摘要

Peak-to-Average Power Ratio (PAPR) reduction is a challenging task in Generalized Frequency Division Multiplexing (GFDM) systems, and it leads to in-band distortion and out-of-band distortions due to the non-linearity of the high-power amplifiers. To address the PAPR issue in GFDM systems, several methods have been employed. However, the most significant limitations of these techniques are their complex implementation and their extensive usage of control parameters. Partial Transmit Sequence (PTS) is a highly outstanding technique for PAPR reduction, but it is concerned with high complexity due to its meticulous searching phase factor. In this research, a hybrid PTS based enhanced squirrel search algorithm with a random phase sequence matrix (PTS-ESSA-RPSM) reduction model is proposed to overwhelm high PAPR problems in MIMO-GFDM systems. The dominant aspiration of our proposed approach is to attain an optimum phase sequence matrix to reduce PAPR and Computational Complexity (CC) instantaneously. The problem can be tackled by the incorporation of PTS with the proposed ESSA optimized RPSM approach to reclaim the optimal phase factor by the reduction of PAPR, CC, and faster convergence rate. The proposed method is validated with other relevant techniques by measuring Complementary Cumulative Density Function (CCDF), PAPR, and SNR by varying symbols, subcarriers, and oversampling factors. When compared to conventional methods, the proposed strategy improves PAPR by 20–50% across a range of CCDF levels, with the lowest PAPR values observed. At the CCDF $10^{ - 2}$ $10^{- 2}$ , the proposed method achieves approximately 3 dB in PAPR. Reductions in out-of-band emissions of 23–60% at various IBO levels validate the capacity of the proposed approach to reduce spectral leakage. ESSA is a very effective optimization strategy since it converges rapidly in about 100 iterations and achieves a final PAPR that is 25–62.5% lower than other optimization strategies. According to the simulation findings, it can be concluded that the proposed model minimizes PAPR very efficiently without increasing the system’s complexity.