Filtered Non-Orthogonal Multiple Access (F-NOMA) is a multi-carrier wave form and is considered a suitable contender for 5G radio. Peak to average power ratio (PAPR) is regarded as a major hurdle in the NOMA wave form because it hampers the efficiency of the power amplifier of the NOMA transmitter. In this study, a novel selective mapping (SLM) algorithm is used to minimize the PAPR of the NOMA. The conventional SLM increases the intricacy of the structure, and the projected SLM algorithm is applied to the transmitter part of the F-NOMA. Furthermore, we evaluate the performance of SLM on F-NOMA for 16, 64, and 256-Quadrature Amplitude Modulation (QAM) transmission methods. The parameters such as Bit Error Rate (BER), PAPR, power spectral density (PSD), and complexity are estimated and compared with different transmission patterns. The simulation outcomes of the work reveal that the optimal PAPR can be achieved by selecting the sub-block (S) and phase rotation elements (Ps). PAPR in F-NOMA achieves 1 dB gain in different QAM transmissions and its saving performance is 70.07%; however, complexity increases with an increase in modulation order.
Non-orthogonal multiple access (NOMA) is a great contender for future cellular modulation due to its desirable properties like massive connectivity, high data rate transmission, and high spectral efficiency. However, its peak-to-average power ratio (PAPR) is significant, which becomes a significant disadvantage for the efficient operability of the NOMA waveform compared to current techniques. Several PAPR reduction algorithms like selective mapping (SLM), partial transmission sequence (PTS), and companding techniques have been proposed to lower the PAPR of multicarrier waveforms (MCWs). PTS reduces the PAPR but has high complexity. On the other hand, SLM has a less complex framework, but its PAPR performance is not as efficient as PTS. Companding methods reduce the PAPR by compressing the signals at the transmitter, which unfortunately reduces the dynamic range of the signal. In this work, we propose a hybrid algorithm (SLM + PTS) with a companding method for the first time for the NOMA waveform, which efficiently reduces the PAPR with low computational complexity. Furthermore, we compare the performances of a host of candidate algorithms like SLM, PTS, hybrid (SLM + PTS), hybrid + A law (SLM-PTS-A law), and hybrid + Mu law (SLM-PTS-Mu law). The results of the experiments show that the hybrid + Mu law did a better job than the existing PAPR reduction algorithms.
This study presents a comprehensive analysis of the throughput performance, spectrum efficiency, and block error rate (BLER) of optical non-orthogonal multiple access (O-NOMA) waveforms using 16-quadrature amplitude modulation (QAM), 64-QAM, and 256-QAM modulation schemes. The aim is to assess the trade-offs between data rate, spectral efficiency, and error performance in O-NOMA systems. The analysis reveals that higher-order modulations, such as 64-QAM and 256-QAM, offer higher data rates and improved spectrum efficiency compared to 16-QAM. Furthermore, the study investigates the spectrum performance of the O-NOMA waveforms. The results indicate that higher-order modulations may utilise the spectrum more efficiently, maximising the data throughput within the available bandwidth. Moreover, the BLER analysis provides insights into the error performance of the O-NOMA waveforms. It quantifies the probability of errors occurring in a block of transmitted data and evaluates the system’s reliability. The analysis reveals that 256-QAM O-NOMA achieves lower BLER and high throughput in uplink and downlink as compared with the 16 and 64-QAM O-NOMA frameworks.
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