Spreading the Wave: Low-Complexity PAPR Reduction for AFDM and OCDM in 6G Networks

TL;DR

This paper presents a low-complexity, unified premodulation data spreading method to significantly reduce PAPR in OCDM and AFDM systems, enhancing energy efficiency and robustness for 6G networks.

Contribution

It introduces a novel PAPR reduction technique using four spreading transforms that requires minimal computation and no side information, outperforming traditional high-complexity methods.

Findings

Significant PAPR reduction achieved with low computational complexity.

Improved phase selectivity and robustness in doubly dispersive channels.

Enhanced energy efficiency and scalability for IoT sensor networks.

Abstract

High Peak-to-Average Power Ratio (PAPR) is still a common issue in multicarrier signal modulation systems such as Orthogonal Chirp Division Multiplexing (OCDM) and Affine Frequency Division Multiplexing (AFDM), which are envisioned to play a central role in 6G networks. To this end, this paper aims to investigate a novel and low-complexity solution towards minimizing the PAPR with the aid of a unified premodulation data spreading paradigm. It analyze four spreading techniques namely, Walsh-Hadamard transform (WHT), Discrete Cosine transform (DCT), Zadoff-Chu transform (ZC), and Interleaved Discrete Fourier transform (IDFT), which assist in preallocating energy prior to OCDM and AFDM modulation. The proposed method takes advantage of the inherent characteristics of chirp-based modulation to achieve a notable reduction in PAPR at minimal computational load and no side information as compared to past solutions, such as Partial Transmit Sequence (PTS) or Selected Mapping (SLM), which suffers with a high computational complexity. The proposed method has an additional benefit of achieving an improvement in phase selectivity by increasing chirp parameters of AFDM and quadratic phase of OCDM, which amplifies the robustness in doubly dispersive channels. It further reduces interference by smoothing the output spread signal. The analytical and simulation results demonstrate an improvement in the overall energy efficiency and scalability of large ioT sensor networks.