Please login to be able to save your searches and receive alerts for new content matching your search criteria.
Nonorthogonal multiple access (NOMA) waveforms need to be tested for their performance and effectiveness using partial transmit sequence (PTS) techniques and peak-to-average power ratio (PAPR) analysis. This is an important part of the advanced radio framework. This paper examines the PAPR features of NOMA systems using PTS with different sub-carrier configurations (64, 256, and 512). We examine BER, PSD, and PAPR distributions by modeling NOMA waveforms with PTS to understand the impact of different sub-carrier counts on signal complexity and efficiency. The findings shed light on how sub-carrier quantity affects PAPR statistics and offer guidance on the best way to design NOMA waveforms for improved spectral efficiency and reduced signal distortion. The simulation results show that by lowering the PAPR while maintaining the BER performance, the suggested system performs better than the traditional PAPR algorithm.
Optical orthogonal time frequency space (OTFS) is better at handling Doppler shifts and multipath fading, making signals more reliable and valuable in places with much movement beyond the fifth generation (B5G). Using practical power amplifiers at the transmitter causes power inefficiency and signal distortion because of the OTFS system’s high peak-to-average power ratio (PAPR), severely reducing system efficiency. Combining partial transmit sequence (PTS) and selective mapping (SLM), a technique known as PTS+SLM, reduces peak power. While SLM generates numerous phase-modulated signal candidates and chooses the one with the lowest PAPR, PTS separates the signal into sub-blocks and optimizes their phases to decrease peak power. With few changes to the signal structure, this dual strategy effectively reduces PAPR while improving power spectral density (PSD) efficiency. As a result, we ensure the accuracy and dependability of the transferred data by maintaining the bit error rate (BER). Fractal optimization methods could be applied to these algorithms. For example, fractal-inspired optimization techniques might be used to explore the phase space more effectively or to discover new phase sequences that result in lower PAPR. According to the simulation findings, the suggested PTS+SLM method works better than the traditional PTS and SLM methods.