A Novel PAPR reduction method using Schur decomposition in CAZAC transform based precoded OFDM for Beyond 5G Applications

In the recent times, the demand for better spectral efficiency and lower power consumption has increased significantly. As a result, effective methods for reducing the peak-to-average power ratio (PAPR) are crucial. Orthogonal frequency division multiplexing (OFDM) is a fundamental technology in 5G and Beyond 5G (B5G) systems. To enhance its performance, implementing an efficient PAPR reduction technique is necessary. Based upon these grounds, this paper introduces a novel PAPR reduction method that integrates Schur decomposition with Walsh–Hadamard Transform (WHT) and Constant Amplitude Zero Auto-Correlation (CAZAC) transform in a precoded OFDM system. The mathematical expression of the time-domain signal for the proposed Schur-based WHT＋CAZAC-OFDM system is derived. The simulation results of this work unveil that the proposed SCHUR＋WHT＋CAZAC-based OFDM system significantly minimizes PAPR by exhibiting a remarkable PAPR reduction of 8.736 dB and 9.86 dB compared to conventional OFDM over AWGN and Rayleigh Fading channels . In addition, the proposed system enhances spectral containment, and reduces spectral regrowth with substantial improvement in power spectral density (PSD) performance. A comparative analysis with singular value decomposition (SVD) and QR decomposition-based approaches is also performed. The results indicate that all three techniques effectively reduce PAPR. However, the SCHUR＋WHT＋CAZAC method achieves a better balance between computational complexity and overall performance. These advancements make it highly suitable for various B5G applications, including ultra-reliable low-latency communications (URLLC), massive machine-type communications (mMTC), and enhanced mobile broadband (eMBB), where high data rates, low latency, and reliable connectivity are crucial.