基于线性调频参数调优的AFDM中PAPR与OOBE的联合降低

中文摘要 AI 辅助

本文通过选择预线性调频参数c₂，解决了仿射频分复用（AFDM）系统中峰值平均功率比（PAPR）与带外辐射（OOBE）的联合降低问题。现有方法通常独立优化PAPR或OOBE，而所提方法同时考虑这两个指标。为此，引入结合PAPR与OOBE的加权代价函数，以评估两个目标间的权衡。随后，采用受选映射（SLM）技术启发的预线性调频选择方案，从有限候选集中确定最优c₂值，在离散集合内得到帕累托最优工作点。仿真结果表明，与传统AFDM相比，所提方法可同时降低PAPR与OOBE；此外，其性能与针对单一目标优化的方法接近，仅在PAPR降低上有约1dB的衰减，在OOBE抑制上有约2-3dB的衰减。

英文摘要

This paper addresses the joint reduction of the peak-to-average power ratio (PAPR) and out-of-band emissions (OOBE) in affine frequency division multiplexing (AFDM) systems by selecting the pre-chirp parameter c2. While existing approaches typically optimize either PAPR or OOBE independently, the proposed method jointly considers both metrics. To this end, a weighted cost function combining PAPR and OOBE is introduced to evaluate the trade-off between the two objectives. A pre-chirp selection scheme, inspired by the selected mapping (SLM) technique, is then employed to identify the optimal c2 value from a finite set of candidates, yielding a Pareto-optimal operating point within a discrete set. Simulation results demonstrate that the proposed approach simultaneously reduces both PAPR and OOBE compared with conventional AFDM. Moreover, its performance remains close to that of methods specifically optimized for a single objective, with only about a 1 dB degradation in PAPR reduction and a 2-3 dB degradation in OOBE suppression.

发表机构

• B-com
• Constructor University（康斯特克大学）
• University of Essex（埃塞克斯大学）

机构由 AI 辅助整理，请以论文原文为准。