Non-orthogonal multiple access (NOMA) is a strong contender multicarrier waveform technique for the fifth generation (5G) communication system. The high peak-to-average power ratio (PAPR) is a serious concern in designing the NOMA waveform. However, the arrangement of NOMA is different from the orthogonal frequency division multiplexing. Thus, traditional reduction methods cannot be applied to NOMA. A partial transmission sequence (PTS) is commonly utilized to minimize the PAPR of the transmitting NOMA symbol. The choice phase aspect in the PTS is the only non-linear optimization obstacle that creates a huge computational complication due to the respective non-carrying sub-blocks in the unitary NOMA symbol. In this study, an efficient phase factor is proposed by presenting a novel bacterial foraging optimization algorithm (BFOA) for PTS (BFOA-PTS). The PAPR minimization is accomplished in a two-stage process. In the initial stage, PTS is applied to the NOMA signal, resulting in the partition of the NOMA signal into an act of sub-blocks. In the second stage, the best phase factor is generated using BFOA. The performance of the proposed BFOA-PTS is thoroughly investigated and compared to the traditional PTS. The simulation outcomes reveal that the BFOA-PTS efficiently optimizes the PAPR performance with inconsequential complexity. The proposed method can significantly offer a gain of 4.1 dB and low complexity compared with the traditional OFDM.

Orthogonal frequency division multiplexing (OFDM) is a modern multicarrier scheme (MCS) utilized in the fourth generation (4G) communication system. However, OFDM possesses several disadvantages, such as loss of bandwidth due to the employment of cyclic prefix, complex calculations due to the frequency error, incapable of handling huge volume of data traffic, and leakage of the spectrum [

Projects a peak power minimization algorithm that can be applied to all advanced waveforms.

Proposes a novel scheme that combines PTS and BFOA to enhance throughput performance.

The projected method realized a gain of 4.1 dB and low complexity compared with the OFDM.

The rest of this article is organized as follows. The key features and significance of projected system are provided in Section 2. Then, recent regulatory and standard body activities aimed at fostering future wireless systems are described in Section 3.

The schematic of NOMA is shown in

Symbol | Definition |
---|---|

Phase factors | |

Sub-blocks | |

NOMA transmitted signal | |

Sub-carriers | |

Complex pass-band modulation signal | |

Response of the Chebyshev filter | |

Complementary Cumulative distribution function | |

_{u} |
NOMA sub-blocks |

Peak power estimation | |

Phase sequence | |

Optimize PTS signal |

It is designed based on Chebyshev filter, SC, and inverse fast Fourier transforms (IFFT), SIC, and fast Fourier transform (FFT) [

where

PAPR is deliberated to specify the threshold variation of the peak power of a broadcast signal. Hence, the change in the largest value of the NOMA signal is estimated by PAPR. The complex NOMA signal can be written as

where

Traditionally, PAPR is defined in terms of dB as

The performance of reduction techniques is estimated, and the complementary cumulative distribution function (CCDF) of PAPR is calculated as

BFOA is based on _{n}_{n}_{n}_{n}

The schematic of the proposed BFOA-PTS is shown in

_{u}

where _{u}

In the proposed method, the food nutrient is analogous to the phase sequence:

where ^{U −1} combinations can be considered to find the ideal

_{uBFOA}

The present work is analyzed using MATLAB. The constraints used in the model are shown in

Parameters | Value |
---|---|

Multicarrier scheme | NOMA |

Filter | Chebyshev |

Transmission scheme | 256-QAM |

Number of sub-carriers ( |
256 |

Bandwidth | 18 MHz |

Number of sub-blocks ( |
16, 32 |

(Phase factor) |
2, 4, 8, 16, 32 |

The number of multiplications required in the projected method is ^{U −1}. The required multiplication and addition for PTS are 4

The performance of the projected work is evaluated. The CCDF of NOMA PAPR for ^{−3} CCDF, the efficiency of 16.6% in the PAPR is achieved by the PTS. The efficiencies of 33%, 35%, 48%, 62.5%, and 67% are observed for

The CCDF of NOMA PAPR for ^{−3} CCDF, the efficiencies of 16.6%, 35%, 41%, 50%, 66.6%, and 83.3% are observed for PTS when

The throughput of the filter bank multicarrier (FBMC) is analyzed, and the BER graph is depicted in ^{−3} at 12 dB SNR. At 10^{−3} dB, the gains of 2.2, 4.06, 5.8, 6.6, 7.8, and 9 dB are achieved for PTS when

At the BER of 10^{−3}, the gain of 2.4 dB is achieved for PTS, as shown in

At 10^{−3} CCDF, the PAPR of NOMA and OFDM is 12 and 13.2 dB, without applying the reduction algorithm, as shown in ^{−3} CCDF, the PAPR is reduced to 2.9 dB for FBMC-BFOA-PTS

At the BER of 10^{−3}, the SNR of NOMA and OFDM is 12 and 13.2 dB, without applying the reduction algorithm, as shown in ^{−3} is accomplished at 2.1 dB for FBMC-BFOA-PTS

A novel PTS-BFOA PAPR minimization method attuned with advanced 5G waveform techniques is proposed in this study. The proposed method is grounded along with the combination of PTS and BFOA. The PAPR minimization is accomplished in a two-stage process. In the initial stage, PTS is applied to the NOMA signal, resulting in the partition of the NOMA signal into an act of sub-blocks. In the second stage, the best phase factor is generated using BFOA. The sub-blocks are weighted with different combinations of ^{U −1}, where low PAPR is obtained. Therefore, the PAPR performance is enhanced, and complexity is reduced by selecting different values of

The authors would like to thanks the editors of CMC and anonymous reviewers for their time and reviewing this manuscript. Also, this work was supported by the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University, Saudi Arabia.