Hybrid invasive weed optimization assisted PTS–SLM framework for efficient PAPR reduction in NOMA systems over Rayleigh and Rician channels

Non-Orthogonal Multiple Access (NOMA) is considered a promising multiple access technique for beyond-5G wireless communication systems due to its ability to improve spectral efficiency and support massive connectivity. However, the multi-carrier nature of NOMA signals results in a high Peak-to-Average Power Ratio (PAPR), which degrades power amplifier efficiency and overall system performance. In this paper, a hybrid PAPR reduction framework integrating Invasive Weed Optimization (IWO) with Selective Mapping (SLM) and Partial Transmit Sequence (PTS) is proposed. The IWO algorithm optimizes phase rotation factors and candidate sequences, reducing the search complexity associated with conventional methods. The proposed schemes are evaluated through MATLAB simulations for a downlink NOMA system with 256 subcarriers, 256-QAM modulation, and two users under Rayleigh and Rician fading channels. Performance is analyzed using CCDF, BER, and PSD metrics. At a CCDF of \(\:{10}^{-4}\) , the proposed PTS + IWO scheme achieves a PAPR reduction of approximately 6–9 dB, outperforming conventional PTS and SLM techniques. In addition, the BER performance improves by about 1–3 dB SNR gain, while the power spectral density is reduced to approximately − 700 to − 810 W/MHz, indicating improved spectral containment. These results demonstrate that the proposed hybrid approach effectively reduces PAPR while maintaining signal integrity and spectral efficiency in NOMA systems.