Tone injection (TI) is a promising distortionless PAPR reduction technique that incurs no spectral efficiency loss. However, state-of-the-art TI schemes based on random candidate generation or clipping noise spectrum suffer from fundamental limitations in PAPR performance. In this paper, we propose novel TI schemes compatible with both OFDM and AFDM systems. The proposed schemes iteratively update the TI sequence via a candidate ranking procedure guided by time-domain local peaks. This accurately selects effective candidates while achieving a complexity comparable to that of the fast Fourier transform. Depth-first search is further integrated to enhance PAPR performance by exploiting the tree structure of the process. Simulations demonstrate that the proposed schemes achieve over 1 dB PAPR gain over baseline TI schemes at comparable complexity. The gain is consistent across various numbers of subcarriers under controlled per-iteration complexities, confirming a superior performance-complexity trade-off for both OFDM and AFDM.

翻译：注音法（TI）是一种有前景的无失真PAPR抑制技术，且不造成频谱效率损失。然而，基于随机候选生成或削波噪声频谱的现有最优TI方案在PAPR性能上存在根本性限制。本文提出适用于OFDM和AFDM系统的新型TI方案。该方案通过时域局部峰值引导的候选排名流程迭代更新TI序列，能够精准选择有效候选，同时实现与快速傅里叶变换相当的复杂度。进一步引入深度优先搜索利用过程的树状结构以增强PAPR性能。仿真表明，在相近复杂度下，所提方案相较于基准TI方案实现了超过1 dB的PAPR增益。在受控的每迭代复杂度下，该增益在不同子载波数量下保持稳定，证实了OFDM和AFDM系统在性能-复杂度权衡方面的优越性。