Low Complexity Rotation Algorithm for PAPR Reducing Performance in Partial Transmits Sequence

Alameri, Thamer; Ali, Nabeel Salih; Attiah, Mothana L.; Talib, Mohammed Saad; Mezaal, Jawad Kadhim

doi:10.1007/s11277-021-09400-4

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…Several sub-frames are splits from the PTS input data frame, corresponding phase factor is rotated for each sub-frame that returns phase factors permutation such that combined sub-frames of PAPR are minimized [30,31]. Input data block 𝑋 Partitioned into 𝑉 sub-frames disjoint 𝕏 𝑣 (𝑣 = 1,2, … , 𝑉), as in Eq.…”

Section: Partial Transmit Sequence (Pts)mentioning

confidence: 99%

Prime Learning Ant Lion Optimization with Precoding and Companding for PAPR Reduction in MIMO-OFDM

2022

IJIES

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To meet the increasing demand for wireless applications requires efficient performance in orthogonal frequency division multiplexing (OFDM) and multi-input multi-output (MIMO). The existing methods involve applying various optimization techniques to increase the performance of the partial transmit sequence (PTS) and OFDM system to reduce the peak average to power ratio (PAPR). This research proposes prime learning ant lion optimization (PL-ALO) method to reduce the PAPR and bit error rate (BER) of the system. The tournament selection technique is applied to increase the exploitation related to the best fitness agent that improves the PL-ALO model performance. The tournament selection technique randomly performs tournaments among the best fitness search agent in the system. The square-root raised cosine (SRC) precoding and Mu law companding techniques were applied to improve the efficiency of the system. The comparison between discrete cosine transform (DCT) and fast fourier transform (FFT) techniques was carried out in the performance analysis. The DCT-based method has higher efficiency than FFT-based techniques in the system. The PL-ALO method has higher efficiency than existing techniques of particle swarm optimization (PSO)-grey wolf optimization (GWO) and multi-objective mayfly algorithm (MOMA). The average PAPR of selective mapping (SLM) is 8.243, PTS-ant lion optimization (ALO) is 3.962, MAMO is 5.279, PSO-GWO is 5.854, and PL-ALO is 3.099.

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Section: Partial Transmit Sequence (Pts)mentioning

confidence: 99%

Prime Learning Ant Lion Optimization with Precoding and Companding for PAPR Reduction in MIMO-OFDM

2022

IJIES

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Efficient Crest Factor Reduction Techniques for 5G NR: A Review and a Case Study

Dalwadi¹,

Krishnan²,

Shah³

et al. 2023

Wireless Pers Commun

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A Low-Complexity PTS Technique–based Improved Pso Algorithm for Papr Reduction in Ofdm Systems

et al. 2023

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Partial transmit sequence (PTS) is a potent and distortionless scheme frequently used to lower the high peak-to-average power ratio (PAPR) levels in orthogonal frequency division multiplexing (OFDM) signaling. Although this method effectively reduces the PAPR, its main limitation is the exponential growth in the computational expense caused by the exhaustive search for the optimal complex of rotation factors. This work proposes a suboptimal PTS scheme based on an improved particle swarm optimization (PSO) algorithm. The latter exploits heuristics to find the best-matched weighting factors complex in fewer computations. A comparison against existing techniques ascertains the superior efficiency of the proposed scheme in terms of PAPR mitigation and computational burden.

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Low Complexity Rotation Algorithm for PAPR Reducing Performance in Partial Transmits Sequence

Cited by 3 publications

References 30 publications

Prime Learning Ant Lion Optimization with Precoding and Companding for PAPR Reduction in MIMO-OFDM

Prime Learning Ant Lion Optimization with Precoding and Companding for PAPR Reduction in MIMO-OFDM

Efficient Crest Factor Reduction Techniques for 5G NR: A Review and a Case Study

A Low-Complexity PTS Technique–based Improved Pso Algorithm for Papr Reduction in Ofdm Systems

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