Agile Affine Frequency Division Multiplexing

TL;DR

Agile-AFDM introduces a dynamic, data-aware framework for AFDM waveforms, enabling real-time optimization of parameters to enhance power efficiency, communication reliability, and sensing accuracy in 6G applications.

Contribution

This paper presents Agile-AFDM, a novel adaptive framework that optimizes AFDM parameters in real-time based on channel and data, surpassing static waveform limitations.

Findings

Significant performance improvements over OFDM and static AFDM

Enhanced power efficiency through PAPR minimization

Improved communication reliability and sensing accuracy

Abstract

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.