A BACTERIA FORAGING ALGORITHM-BASED HYBRID A-LAW AND PTS PAPR REDUCTION METHOD FOR BEYOND 5G WAVEFORM

Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong, Nada Alzaben, Abdulsamad Ebrahim Yahya, Siwar Ben Haj Hassine, Nasir Albalawee and Samah Al Zanin
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Arun Kumar: Department of Electronics and Communication Engineering, New Horizon College of Engineering, Bengaluru 560103, Karnataka, India
Nishant Gaur: ��Department of Physics, JECRC University, Jaipur 303905, Rajasthan, India
Aziz Nanthaamornphong: ��College of Computing, Prince of Songkla University, Phuket Campus, Phuket, Thailand
Nada Alzaben: �Department of Computer Science, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh 11671, Saudi Arabia
Abdulsamad Ebrahim Yahya: �Department of Information Technology, College of Computing and Information Technology, Northern Border University Arar, Saudi Arabia
Siwar Ben Haj Hassine: ��Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia
Nasir Albalawee: *Department of Law, Faculty of Law, Jadara University, Irbid, Jordan
Samah Al Zanin: ��†Department of Computer Science, Applied College, Prince Sattam bin Abdulaziz University, Kharj, Saudi Arabia

FRACTALS (fractals), 2024, vol. 32, issue 09n10, 1-20

Abstract: One of the most advanced waveforms available in the beyond-fifth-generation radio (B5GR) framework is nonorthogonal multiple access (NOMA). The power amplifier (PA) of the NOMA structure performs less efficiently when the signal is strong and the peak-to-average power ratio (PAPR) is high. This study applies a hybrid algorithm to the NOMA structure, combining fractal partial transmit sequence (PTS), A-law companding, and the bacterial foraging algorithm (BFA). Fractals are known for their self-repeating structures at different scales, allowing for efficient coverage and exploration of space. Fractals enhance the bacteria foraging algorithm (BFA) by improving search efficiency, enabling better exploration of complex, multi-dimensional optimization landscapes. Similarly, BFA balances exploring the search in promising areas. We utilized BFA to achieve optimal phase factors for the PTS algorithm and applied A-Law companding to the NOMA symbols to further enhance the structure’s performance. The intermediate computational complexity in the Rician and Rayleigh channels improves PAPR, bit error rate (BER), and power spectral density performance. Simulation results reveal that the performance of the proposed hybrid method is superior to that of existing PAPR reduction algorithms and substantially enhances the efficiency of NOMA.

Keywords: Fractal-BFA; Fractal Alaw-PTS; Beyond 5G; Nonlinear PAPR; Genetic Algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0218348X25400043

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