A novel hybrid genetic algorithm to reduce the peak-to-average power ratio of OFDM signals

Sharifi, Abbas Ali; Aghdam, Mehdi Hosseinzadeh

doi:10.1016/j.compeleceng.2019.106498

Cited by 14 publications

(11 citation statements)

References 23 publications

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“…In this subsection, we compare the proposed method with PTS and some of its variants: Hybrid Genetic Algorithm PTS (HGA-PTS) [15], Genetic Algorithm PTS (GA-PTS) [34], Random Search PTS (RS) [38], Iterative flipping PTS (IPTS) [38], PSO-PTS [16], and Optimal PTS (OPTS) with an exhaustive search [15]. The parameters of PTS are as follows: The performance in terms of the PAPR is depicted in Figure 19.…”

Section: Papr Comparison With Pts Variantsmentioning

confidence: 99%

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Palm Date Leaf Clipping: A New Method to Reduce PAPR in OFDM Systems

et al. 2020

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Orthogonal frequency division multiplexing (OFDM) is the key technology used in high-speed communication systems. One of the major drawbacks of OFDM systems is the high peak-to-average power ratio (PAPR) of the transmitted signal. The transmitted signal with a high PAPR requires a very large linear range of the Power Amplifier (PA) on the transmitter side. In this paper, we propose and study a new clipping method named Palm Clipping (Palm date leaf) based on hyperbolic cosine. To evaluate and analyze its performance in terms of the PAPR and Bit Error Rate (BER), we performed some computer simulations by varying the Clipping Ratio (CR) and modulation schemes. The obtained results show that it is possible to achieve a gain of between 7 and 9 dB in terms of PAPR reduction depending on the type of modulation. In addition, comparison with several techniques in terms of PAPR and BER shows that our method is a strong alternative that can be adopted as a PAPR reduction technique for OFDM-based communication systems.

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Section: Papr Comparison With Pts Variantsmentioning

confidence: 99%

“…It is known that PTS is a popular method used to reduce PAPR in OFDM systems. Several variants of PTS have been proposed, such as Hybrid Genetic Algorithm Partial Transmit Sequences (HGA-PTS) [15], Particle Swarm Optimization Partial Transmit Sequences (PSO-PTS) [16], and Genetic Algorithm Partial Transmit Sequences (GA-PTS) [17].…”

Section: Introductionmentioning

confidence: 99%

Palm Date Leaf Clipping: A New Method to Reduce PAPR in OFDM Systems

et al. 2020

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“…The phase rotation factors are determined to reduce the PAPR of the compounded time-domain signal of all subblocks. 27 The goal of the PTS is to choose the phase rotation factors sequence that decreases the PAPR of the obtained signal, x, as follows:…”

Section: Ofdm System Modelmentioning

confidence: 99%

“…Thus, the power distribution is a central chi‐square distribution with two degrees of freedom. So, the CCDF is as 27 :

C C D F = 1 - {false(1 - e x p false(- P A P R_{0} false) false)}^{N L} .

…”

Section: Ofdm System Modelmentioning

confidence: 99%

“…Although GWO has a high convergence rate, it cannot significantly reduce PAPR. Also, several optimization approaches based on the genetic algorithm (GA), 25,26 hybrid GA (HGA), 27 particle swarm optimization (PSO), 28 tabu search, 29 differential evolution algorithm, 30 backtracking search algorithm 31,32 have been developed for PAPR reduction so far.…”

Section: Introductionmentioning

confidence: 99%

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A novel ant colony optimization algorithm for PAPR reduction of OFDM signals

Aghdam

Sharifi

2020

Int J Communication

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SummaryThe high peak‐to‐average power ratio (PAPR) is the main challenge of orthogonal frequency division multiplexing (OFDM) systems. Partial transmit sequence (PTS) is a useful approach to diminish the PAPR. Although the PTS approach significantly decreases the PAPR, it requires to explore all possible sequences of phase weighting factors. Hence, the computational cost exponentially increases with the number of divided subblocks. This paper proposes a novel PTS technique based on ant colony optimization (ACO) to diminish the high PAPR and computational cost of OFDM systems. By the new representation of phase factors as a graph, the improved ACO algorithm is combined with the PTS method to explore the optimal compound of the phase rotation factors. Simulation results represent that the proposed ACO‐based PTS approach significantly reduces the PAPR and improves the computational cost at the same time. A comparative analysis of the other meta‐heuristics shows that the ACO‐PTS approach outperforms the genetic algorithm, particle swarm optimization, and gray wolf optimization in terms of reducing PAPR.

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