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<p>Non-Orthogonal Multiple Access (NOMA) is a key technology that makes sixth-generation (6G) radio systems possible because it can support numerous connections and improve spectral efficiency. The superposition of multiuser signals in the power domain, however, greatly increases the peak-to-average power ratio (PAPR), making power amplifiers less efficient and degrading performance, especially in systems with numerous subcarriers. This study proposes a binary–real coded genetic algorithm (BC–RCGA) framework based on a partial transmit sequence (PTS) to reduce PAPR in NOMA waveforms. The proposed method optimizes both discrete phase rotation factors and continuous control parameters within a single evolutionary structure, which is different from traditional GA-based PTS schemes that only optimize discrete phase rotation factors. This makes the search process faster and less complicated. The proposed framework is tested in an OFDM–NOMA system with 128, 256, and 512 subcarriers using quadrature amplitude modulation over additive white Gaussian noise channels, considering real-world power-domain user superposition. Simulation results indicate that, at a CCDF of 10⁻³, the proposed BC–RCGA–PTS attains a PAPR reduction of approximately 4–6 dB in comparison to conventional NOMA and 1–2 dB relative to GA–PTS and particle swarm optimization (PSO)-based PTS schemes. The BER performance is also maintained and improved, reaching a BER of 10⁻³ at an SNR gain of up to 6 dB compared to regular NOMA. Complexity analysis shows that the proposed method reduces fitness evaluations by more than 35% compared to GA–PTS; however, it adds some extra processing time during evolution. The results demonstrate that the proposed BC–RCGA–PTS is a practical and effective approach to reducing PAPR in NOMA-enabled 6G radio systems.</p>

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PAPR reduction in NOMA waveforms using PTS-based binary–real coded genetic algorithm for 6G radio systems

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月1日

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  • Arun Kumar,
  • Sharifah Sakinah Syed Ahmad,
  • Venkatachalam Revathi,
  • Nishant Gaur,
  • Prashanta Chandra Pradhan,
  • Aziz Nanthaamornphong

摘要

Non-Orthogonal Multiple Access (NOMA) is a key technology that makes sixth-generation (6G) radio systems possible because it can support numerous connections and improve spectral efficiency. The superposition of multiuser signals in the power domain, however, greatly increases the peak-to-average power ratio (PAPR), making power amplifiers less efficient and degrading performance, especially in systems with numerous subcarriers. This study proposes a binary–real coded genetic algorithm (BC–RCGA) framework based on a partial transmit sequence (PTS) to reduce PAPR in NOMA waveforms. The proposed method optimizes both discrete phase rotation factors and continuous control parameters within a single evolutionary structure, which is different from traditional GA-based PTS schemes that only optimize discrete phase rotation factors. This makes the search process faster and less complicated. The proposed framework is tested in an OFDM–NOMA system with 128, 256, and 512 subcarriers using quadrature amplitude modulation over additive white Gaussian noise channels, considering real-world power-domain user superposition. Simulation results indicate that, at a CCDF of 10⁻³, the proposed BC–RCGA–PTS attains a PAPR reduction of approximately 4–6 dB in comparison to conventional NOMA and 1–2 dB relative to GA–PTS and particle swarm optimization (PSO)-based PTS schemes. The BER performance is also maintained and improved, reaching a BER of 10⁻³ at an SNR gain of up to 6 dB compared to regular NOMA. Complexity analysis shows that the proposed method reduces fitness evaluations by more than 35% compared to GA–PTS; however, it adds some extra processing time during evolution. The results demonstrate that the proposed BC–RCGA–PTS is a practical and effective approach to reducing PAPR in NOMA-enabled 6G radio systems.