PAPR reduction using twin symbol hybrid optimization-based PTS and multi-chaotic-DFT sequence-based encryption in CP-OFDM system

Sarkar, Mrinmoy; Kumar, Asok; Maji, Bansibadan

doi:10.1007/s11107-020-00923-7

Cited by 12 publications

(7 citation statements)

References 22 publications

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“…The improved ACO method has lower convergence, lower exploitation rate and stagnation phase. Sarkar [15] applied twin symbol hybrid optimization based on cyclic prefix OFDM and PTS method. The slap swarm optimization (SSO) and bald eagle search (BES) are applied to optimally analyze the PTS method phase factor.…”

Section: Literature Surveymentioning

confidence: 99%

“…If the ant's fitness value is better than the antlion's fitness, the ant antlion position is updated as the ant position, as in Eq. (15).…”

Section: Prime Learning Ant Lion Optimization For Ptsmentioning

confidence: 99%

“…Commonly applied algorithms for PAPR reduction are bat inspired algorithm (BA), genetic algorithm (GA), grey wolf optimizer (GWO), whale optimization algorithm International Journal of Intelligent Engineering and Systems, Vol. 15 (WOA), and artificial bee colony (ABC), and particle swarm optimization [6,7]. high cubic metric (CM) is mitigated using partial transmit sequence (PTS) in OFDM signals and original PTS faces high computational complexity due to phase factor possible combinations.…”

Section: Introductionmentioning

confidence: 99%

“…International Journal of Intelligent Engineering and Systems, Vol 15,. No.5, 2022 DOI: 10.22266/ijies2022.1031.38best search agents to increase the exploitation.…”

mentioning

confidence: 99%

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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: Literature Surveymentioning

confidence: 99%

“…If the ant's fitness value is better than the antlion's fitness, the ant antlion position is updated as the ant position, as in Eq. (15).…”

Section: Prime Learning Ant Lion Optimization For Ptsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…International Journal of Intelligent Engineering and Systems, Vol 15,. No.5, 2022 DOI: 10.22266/ijies2022.1031.38best search agents to increase the exploitation.…”

mentioning

confidence: 99%

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

2022

IJIES

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“…Sarkar et al [13] presented a Twin Symbol Hybrid Optimization utilized as a fundamental PTS (TSHO-PTS) technique of Cyclic Prefix-OFDM (CP-OFDM). It attains the needs of 5G telecommunication standard.…”

Section: Literature Reviewmentioning

confidence: 99%

Novel Selective Mapping with Oppositional Hosted Cuckoo Optimization Algorithm for PAPR Reduction in 5G UFMC Systems

Jayamathi*¹,

Jayasankar

Kumar

2022

Teh. vjesn.

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In recent times, there is a continuous requirement of achieving high data rates owing to an increase in the number of devices and significant demand for various services with maximum reliability and minimum delay. It results in the development of fifth generation (5G) to offer better services with enhanced data rate. Recently, a major alternative to OFDM technology for 5G networks called universal filtered multi-carrier (UFMC) is presented where every individual sub-band is filtered that reduces the OOB radiation and eliminates guard band. But high peak-to-average power ratio (PAPR) is a crucial issue which arises from the utilization of several subcarriers to generate the time domain transmission signal. For resolving this issue, this paper presents a novel selective mapping with oppositional hosted cuckoo optimization (SM-OHOCO) algorithm for PAPR reduction in 5G UFMC systems. In the SM-OHOCO algorithm, rather than the generation of several random phase sequences, SM-OHOCO algorithm is performed iteratively to attain a better solution with few searching rounds, showing the novelty of the work. As the optimization of phase sequence in the SLM technique is considered as an NP hard optimization problem, the OHOCO algorithm is applied, which is derived by incorporating the concepts of the HOCO algorithm with oppositional based learning (OBL) strategy. To validate the effective performance of the proposed SM-OHOCO algorithm, an extensive experimental analysis is performed to highlight the improved performance in 5G networks. The resultant values pointed out the superior outcome of the proposed SM-OHOCO algorithm over the other existing methods in terms of distinct measures

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PTS with Phase Factor-Based Reptile Search Algorithm and Hybrid Coding Approach for PAPR and BER Reduction in MIMO-OFDM

Krishna Reddy,

Merlin Sheeba

2023

Advances in Intelligent Systems and Computing

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PAPR reduction using twin symbol hybrid optimization-based PTS and multi-chaotic-DFT sequence-based encryption in CP-OFDM system

Cited by 12 publications

References 22 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

Novel Selective Mapping with Oppositional Hosted Cuckoo Optimization Algorithm for PAPR Reduction in 5G UFMC Systems

PTS with Phase Factor-Based Reptile Search Algorithm and Hybrid Coding Approach for PAPR and BER Reduction in MIMO-OFDM

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