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

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. [ABSTRACT FROM AUTHOR]