敏捷仿射频分复用技术 (Agile Affine Frequency Division Multiplexing)

The advancement to 6G calls for waveforms that transcend static robustness to achieve intelligent adaptability. Affine Frequency Division Multiplexing (AFDM), despite its strength in doubly-dispersive channels, has been confined by chirp parameters optimized for worst-case scenarios. This paper shatters this limitation with Agile-AFDM, a novel framework that endows AFDM with dynamic, data-aware intelligence. By redefining chirp parameters as optimizable variables for each transmission block based on real-time channel and data information, Agile-AFDM transforms into an adaptive platform. It can actively reconfigure its waveform to minimize peak-to-average power ratio (PAPR) for power efficiency, suppress inter-carrier interference (ICI) for communication reliability, or reduce Cramer-Rao bound (CRLB) for sensing accuracy. This paradigm shift from a static, one-size-fits-all waveform to a context-aware signal designer is made practical by efficient, tailored optimization algorithms. Comprehensive simulations demonstrate that this capability delivers significant performance gains across all metrics, surpassing conventional OFDM and static AFDM. Agile-AFDM, therefore, offers a crucial step forward in the design of agile waveforms for 6G and beyond.

翻译：面向6G的发展需求，亟需超越静态鲁棒性、实现智能适应性的波形技术。仿射频分复用（AFDM）虽然在双弥散信道中表现出色，但其啁啾参数长期以来受限于针对最差场景的优化设计，导致灵活性不足。本文通过提出Agile-AFDM这一新颖框架，突破了这一限制，赋予AFDM动态、数据感知的智能能力。该框架将啁啾参数重新定义为每个传输块中可根据实时信道与数据信息进行优化的变量，从而使AFDM转变为自适应平台。Agile-AFDM能够主动重构波形，以降低峰均功率比（PAPR）从而提升功率效率，抑制载波间干扰（ICI）以增强通信可靠性，或降低克拉美-罗下界（CRLB）以提高感知精度。通过设计高效、定制化的优化算法，这一从静态“一刀切”波形向上下文感知信号设计的范式转变得以实现。综合仿真结果表明，该技术在所有指标上均取得显著性能提升，优于传统OFDM及静态AFDM。因此，Agile-AFDM为面向6G及未来的敏捷波形设计迈出了关键一步。