Enhancing Peak Power Efficiency of 5G and beyond 5G NOMA waveform using Novel Selective Mapping Algorithm

The paper presents a novel approach for mitigating the detrimental effects of the high Peak-to-Average Power Ratio (PAPR) inherent in Non-Orthogonal Multiple Access (NOMA) waveforms using the Selective Mapping (SLM) technique. NOMA, a prominent multiple access scheme in modern wireless communication systems, facilitates concurrent transmission of multiple users over the same time-frequency resource. However, NOMA is susceptible to elevated PAPR, causing efficiency degradation and inter-symbol interference. The proposed method leverages SLM to address the PAPR challenges in NOMA waveforms. By generating a set of diverse phase sequences, SLM constructs alternative versions of the original NOMA signal. The phase sequence resulting in the lowest PAPR is then selected for transmission. This dynamic adaptation significantly reduces the peaks in the transmitted signal, thereby enhancing efficiency, minimizing distortion, and reducing the risk of nonlinear amplification. Extensive simulations are conducted to evaluate the efficiency of the projected procedure. The results demonstrate remarkable PAPR reduction in NOMA waveforms compared to conventional transmission methods. Additionally, the method maintains signal quality, improving the Bit Error Rate (BER), Power spectral density (PSD) and enhancing the overall reliability of the radio framework. The paper concludes with insights into the feasibility of integrating SLM into existing NOMA-enabled systems, offering a promising avenue for optimizing the efficacy of advanced radio networks.